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The Encog Project

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A

actionPerformed(ActionEvent) - Method in class org.encog.util.simple.TrainingDialog: Called when the user clicks the stop button.
ActivationBiPolar - Class in org.encog.neural.activation: BiPolar activation function.
ActivationBiPolar() - Constructor for class org.encog.neural.activation.ActivationBiPolar
ActivationBiPolarPersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the ActivationBiPolar class.
ActivationBiPolarPersistor() - Constructor for class org.encog.persist.persistors.ActivationBiPolarPersistor
ActivationCompetitive - Class in org.encog.neural.activation: An activation function that only allows a specified number, usually one, of the out-bound connection to win.
ActivationCompetitive() - Constructor for class org.encog.neural.activation.ActivationCompetitive: Create a competitive activation function with one winner allowed.
ActivationCompetitive(int) - Constructor for class org.encog.neural.activation.ActivationCompetitive: Create a competitive activation function with the specified maximum number of winners.
ActivationCompetitivePersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the ActivationCompetitivePersistor class.
ActivationCompetitivePersistor() - Constructor for class org.encog.persist.persistors.ActivationCompetitivePersistor
activationFunction(double[]) - Method in class org.encog.neural.activation.ActivationBiPolar: Implements the activation function.
activationFunction(double[]) - Method in class org.encog.neural.activation.ActivationCompetitive: Perform the activation function.
ActivationFunction - Interface in org.encog.neural.activation: This interface allows various activation functions to be used with the neural network.
activationFunction(double[]) - Method in interface org.encog.neural.activation.ActivationFunction: Implements the activation function.
activationFunction(double[]) - Method in class org.encog.neural.activation.ActivationGaussian: Implements the activation function.
activationFunction(double[]) - Method in class org.encog.neural.activation.ActivationLinear: Implements the activation function.
activationFunction(double[]) - Method in class org.encog.neural.activation.ActivationLOG: Implements the activation function.
activationFunction(double[]) - Method in class org.encog.neural.activation.ActivationSigmoid: Implements the activation function.
activationFunction(double[]) - Method in class org.encog.neural.activation.ActivationSIN: Implements the activation function.
activationFunction(double[]) - Method in class org.encog.neural.activation.ActivationSoftMax: Implements the activation function.
activationFunction(double[]) - Method in class org.encog.neural.activation.ActivationTANH: Implements the activation function.
ActivationGaussian - Class in org.encog.neural.activation: An activation function based on the gaussian function.
ActivationGaussian(double, double, double) - Constructor for class org.encog.neural.activation.ActivationGaussian: Create a gaussian activation function.
ActivationGaussianPersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the ActivationGaussian class.
ActivationGaussianPersistor() - Constructor for class org.encog.persist.persistors.ActivationGaussianPersistor
ActivationLinear - Class in org.encog.neural.activation: The Linear layer is really not an activation function at all.
ActivationLinear() - Constructor for class org.encog.neural.activation.ActivationLinear
ActivationLinearPersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the ActivationLinear class.
ActivationLinearPersistor() - Constructor for class org.encog.persist.persistors.ActivationLinearPersistor
ActivationLOG - Class in org.encog.neural.activation: An activation function based on the logarithm function.
ActivationLOG() - Constructor for class org.encog.neural.activation.ActivationLOG
ActivationLOGPersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the ActivationLOG class.
ActivationLOGPersistor() - Constructor for class org.encog.persist.persistors.ActivationLOGPersistor
ActivationSigmoid - Class in org.encog.neural.activation: The sigmoid activation function takes on a sigmoidal shape.
ActivationSigmoid() - Constructor for class org.encog.neural.activation.ActivationSigmoid
ActivationSigmoidPersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the ActivationSigmoid class.
ActivationSigmoidPersistor() - Constructor for class org.encog.persist.persistors.ActivationSigmoidPersistor
ActivationSIN - Class in org.encog.neural.activation: An activation function based on the sin function.
ActivationSIN() - Constructor for class org.encog.neural.activation.ActivationSIN
ActivationSINPersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the ActivationSIN class.
ActivationSINPersistor() - Constructor for class org.encog.persist.persistors.ActivationSINPersistor
ActivationSoftMax - Class in org.encog.neural.activation: The softmax activation function.
ActivationSoftMax() - Constructor for class org.encog.neural.activation.ActivationSoftMax
ActivationSoftMaxPersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the ActivationSoftMax class.
ActivationSoftMaxPersistor() - Constructor for class org.encog.persist.persistors.ActivationSoftMaxPersistor
ActivationTANH - Class in org.encog.neural.activation: The hyperbolic tangent activation function takes the curved shape of the hyperbolic tangent.
ActivationTANH() - Constructor for class org.encog.neural.activation.ActivationTANH
ActivationTANHPersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the ActivationTANH class.
ActivationTANHPersistor() - Constructor for class org.encog.persist.persistors.ActivationTANHPersistor
ActivationUtil - Class in org.encog.neural.activation: Utility classes for activation functions.
ADALINEPattern - Class in org.encog.neural.pattern: Construct an adaline neural network.
ADALINEPattern() - Constructor for class org.encog.neural.pattern.ADALINEPattern
add(int, int, double) - Method in class org.encog.matrix.Matrix: Add a value to one cell in the matrix.
add(Matrix) - Method in class org.encog.matrix.Matrix: Add the specified matrix to this matrix.
add(Matrix, Matrix) - Static method in class org.encog.matrix.MatrixMath: Add two matrixes.
add(int, double) - Method in class org.encog.neural.data.basic.BasicNeuralData: Add a value to the specified index.
add(NeuralData) - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Add input to the training set with no expected output.
add(NeuralData, NeuralData) - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Add input and expected output.
add(NeuralDataPair) - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Add a neural data pair to the list.
add(int, double) - Method in class org.encog.neural.data.bipolar.BiPolarNeuralData: This will throw an error, as "add" is not supported for bipolar.
add(NeuralData) - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet: Add only input data, for an unsupervised dataset.
add(NeuralData, NeuralData) - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet: Add both the input and ideal data.
add(NeuralDataPair) - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet: Add a data pair of both input and ideal data.
add(NeuralData) - Method in class org.encog.neural.data.csv.CSVNeuralDataSet: Adds are not supported.
add(NeuralData, NeuralData) - Method in class org.encog.neural.data.csv.CSVNeuralDataSet: Adds are not supported.
add(NeuralDataPair) - Method in class org.encog.neural.data.csv.CSVNeuralDataSet: Adds are not supported.
add(NeuralData) - Method in class org.encog.neural.data.image.ImageNeuralDataSet: Add the specified data, must be an ImageNeuralData class.
add(NeuralData, NeuralData) - Method in class org.encog.neural.data.image.ImageNeuralDataSet: Add the specified input and ideal object to the collection.
add(NeuralDataPair) - Method in class org.encog.neural.data.image.ImageNeuralDataSet: Add input and expected output.
add(int, double) - Method in interface org.encog.neural.data.NeuralData: Add a value to the specified index.
add(NeuralData) - Method in interface org.encog.neural.data.NeuralDataSet: Add a NeuralData object to the dataset.
add(NeuralData, NeuralData) - Method in interface org.encog.neural.data.NeuralDataSet: Add a set of input and ideal data to the dataset.
add(NeuralDataPair) - Method in interface org.encog.neural.data.NeuralDataSet: Add a NeuralData object to the dataset.
add(NeuralData) - Method in class org.encog.neural.data.sql.SQLNeuralDataSet: Adds are not supported.
add(NeuralData, NeuralData) - Method in class org.encog.neural.data.sql.SQLNeuralDataSet: Adds are not supported.
add(NeuralDataPair) - Method in class org.encog.neural.data.sql.SQLNeuralDataSet: Adds are not supported.
add(NeuralData) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Adding directly is not supported.
add(NeuralData, NeuralData) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Adding directly is not supported.
add(NeuralDataPair) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Adding directly is not supported.
add(NeuralData) - Method in class org.encog.neural.data.union.UnionNeuralDataSet: Not supported.
add(NeuralData, NeuralData) - Method in class org.encog.neural.data.union.UnionNeuralDataSet: Not supported.
add(NeuralDataPair) - Method in class org.encog.neural.data.union.UnionNeuralDataSet: Not supported.
add(NeuralData) - Method in class org.encog.neural.data.xml.XMLNeuralDataSet: Adds are not supported, this is a read only data set.
add(NeuralData, NeuralData) - Method in class org.encog.neural.data.xml.XMLNeuralDataSet: Adds are not supported, this is a read only data set.
add(NeuralDataPair) - Method in class org.encog.neural.data.xml.XMLNeuralDataSet: Adds are not supported, this is a read only data set.
add(String, EncogPersistedObject) - Method in class org.encog.persist.EncogPersistedCollection: Add an EncogPersistedObject to the collection.
add(String, File) - Method in class org.encog.util.http.FormUtility: Add a file to a multipart form.
add(String, String) - Method in class org.encog.util.http.FormUtility: Add a regular text field to either a regular or multipart form.
ADD_NOT_SUPPORTED - Static variable in class org.encog.neural.data.csv.CSVNeuralDataSet: Error message indicating that adds are not supported.
ADD_NOT_SUPPORTED - Static variable in class org.encog.neural.data.sql.SQLNeuralDataSet: Error message: adds are not supported.
ADD_NOT_SUPPORTED - Static variable in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Error message: adds are not supported.
ADD_NOT_SUPPORTED - Static variable in class org.encog.neural.data.xml.XMLNeuralDataSet: Error Message: adds are not supported.
addAttribute(String, String) - Method in class org.encog.parse.tags.write.WriteTags: Add an attribute to be written with the next tag.
addCDATA(String) - Method in class org.encog.parse.tags.write.WriteTags: Add CDATA to the output stream.
addContent(DocumentRange) - Method in class org.encog.bot.browse.WebPage: Add to the content collection.
addDataUnit(DataUnit) - Method in class org.encog.bot.browse.WebPage: Add a data unit to the collection.
addDescription(TemporalDataDescription) - Method in class org.encog.neural.data.market.MarketNeuralDataSet: Add one description of the type of market data that we are seeking at each datapoint.
addDescription(TemporalDataDescription) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Add a data description.
addElement(DocumentRange) - Method in class org.encog.bot.browse.range.DocumentRange: Add an element.
addField(OutputFieldGrouped) - Method in class org.encog.normalize.output.BasicOutputFieldGroup: Add a field to this group.
addField(OutputFieldGrouped) - Method in interface org.encog.normalize.output.OutputFieldGroup: Add an output field to the group.
addFieldMapping(int, Field, Object) - Method in class org.encog.persist.persistors.generic.ObjectMapper: Add a field mapping to be resolved later.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.ADALINEPattern: Not used, the ADALINE has no hidden layers, this will throw an error.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.ART1Pattern: This will fail, hidden layers are not supported for this type of network.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.BAMPattern: Unused, a BAM has no hidden layers.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.BoltzmannPattern: Not supported, will throw an exception, Boltzmann networks have no hidden layers.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.CPNPattern: Not used, will throw an error.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.ElmanPattern: Add a hidden layer with the specified number of neurons.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.FeedForwardPattern: Add a hidden layer, with the specified number of neurons.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.HopfieldPattern: Add a hidden layer.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.JordanPattern: Add a hidden layer, there should be only one.
addHiddenLayer(int) - Method in interface org.encog.neural.pattern.NeuralNetworkPattern: Add the specified hidden layer.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.RadialBasisPattern: Add the hidden layer, this should be called once, as a RBF has a single hidden layer.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.RSOMPattern: Add a hidden layer.
addHiddenLayer(int) - Method in class org.encog.neural.pattern.SOMPattern: Add a hidden layer.
addHiddenLayer(int, int) - Method in class org.encog.neural.prune.PruneIncremental: Add a hidden layer's min and max.
addInputField(InputField) - Method in class org.encog.normalize.DataNormalization: Add an input field.
addItem(InputField, double) - Method in class org.encog.normalize.output.nominal.OutputEquilateral: Add a nominal value based on a single value.
addItem(InputField, double, double) - Method in class org.encog.normalize.output.nominal.OutputEquilateral: Add a nominal item based on a range.
addItem(InputField, double) - Method in class org.encog.normalize.output.nominal.OutputOneOf: Add a nominal value specifying a single value, the high and low values will be 0.5 below and 0.5 above.
addItem(InputField, double, double) - Method in class org.encog.normalize.output.nominal.OutputOneOf: Add a nominal item, specify the low and high values.
addLayer(Layer) - Method in class org.encog.neural.networks.BasicNetwork: Add a layer to the neural network.
addLayer(Layer, SynapseType) - Method in class org.encog.neural.networks.BasicNetwork: Add a layer to the neural network.
addLayer(Layer) - Method in interface org.encog.neural.networks.Network: Add a layer to the neural network.
addLayer(Layer, SynapseType) - Method in interface org.encog.neural.networks.Network: Add a layer to the neural network.
addNext(Layer) - Method in class org.encog.neural.networks.layers.BasicLayer: Add a layer as the next layer.
addNext(Layer, SynapseType) - Method in class org.encog.neural.networks.layers.BasicLayer
addNext(Layer) - Method in interface org.encog.neural.networks.layers.Layer: Add a layer to this layer.
addNext(Layer, SynapseType) - Method in interface org.encog.neural.networks.layers.Layer: Add a layer to this layer.
addObjectMapping(int, Object) - Method in class org.encog.persist.persistors.generic.ObjectMapper: Add an object mapping to be resolved later.
addOutputField(OutputField) - Method in class org.encog.normalize.DataNormalization: Add an output field.
addOutputField(OutputField, boolean) - Method in class org.encog.normalize.DataNormalization: Add a field and allow it to be specified as an "ideal output field".
addPattern(NeuralData, NeuralData) - Method in class org.encog.neural.networks.logic.BAMLogic: Add a pattern to the neural network.
addPattern(NeuralData) - Method in class org.encog.neural.networks.logic.HopfieldLogic: Train the neural network for the specified pattern.
addProperty(String, double) - Method in class org.encog.parse.tags.write.WriteTags: Add a property as a double.
addProperty(String, int) - Method in class org.encog.parse.tags.write.WriteTags: Add a property as an integer.
addProperty(String, String) - Method in class org.encog.parse.tags.write.WriteTags: Add a property as a string.
addRange(double, double, double) - Method in class org.encog.normalize.output.mapped.OutputFieldEncode: Add a ranged mapped to a value.
addRange(double, double, boolean) - Method in class org.encog.normalize.segregate.RangeSegregator: Add a range.
addRange(SegregationRange) - Method in class org.encog.normalize.segregate.RangeSegregator: Add a range.
Address - Class in org.encog.bot.browse: A URL address.
Address(URL) - Constructor for class org.encog.bot.browse.Address: Construct the address from a URL.
Address(URL, String) - Constructor for class org.encog.bot.browse.Address: Construct a URL using a perhaps relative URL and a base URL.
addSegregator(Segregator) - Method in class org.encog.normalize.DataNormalization: Add a segregator.
addStrategy(Strategy) - Method in class org.encog.neural.networks.training.BasicTraining: Training strategies can be added to improve the training results.
addStrategy(Strategy) - Method in interface org.encog.neural.networks.training.Train: Training strategies can be added to improve the training results.
addSubset(NeuralDataSet) - Method in class org.encog.neural.data.union.UnionNeuralDataSet: Add a subset.
addSynapse(Synapse) - Method in class org.encog.neural.networks.layers.BasicLayer: Add a synapse to the list of outbound synapses.
addSynapse(Synapse) - Method in interface org.encog.neural.networks.layers.Layer: This method adds a synapse to the neural network.
addText(String) - Method in class org.encog.parse.tags.write.WriteTags: Add text.
adjustWeights() - Method in class org.encog.neural.networks.logic.ART1Logic: Adjust the weights for the pattern just presented.
advance(String) - Method in class org.encog.persist.PersistReader: Advance to the specified object.
advanceObjectsCollection() - Method in class org.encog.persist.PersistReader: Advance to the objects collection.
allConsoleLogging() - Static method in class org.encog.util.logging.Logging: Log everything to the console.
analyze(EncogPersistedObject) - Method in class org.encog.persist.persistors.generic.ObjectTagger: Analyze the specified object and build a reference map.
applyMinMax(double) - Method in class org.encog.normalize.input.BasicInputField: Given the current value, apply to the min and max values.
applyMinMax(double) - Method in interface org.encog.normalize.input.InputField: Update the min and max values for this field with the specified values.
arrayCopy(double[], double[]) - Static method in class org.encog.util.EncogArray: Completely copy one array into another.
arrayToNetwork(double[], BasicNetwork) - Static method in class org.encog.neural.networks.structure.NetworkCODEC: Use an array to populate the memory of the neural network.
ART1Logic - Class in org.encog.neural.networks.logic: Provides the neural logic for an ART1 type network.
ART1Logic() - Constructor for class org.encog.neural.networks.logic.ART1Logic
ART1Pattern - Class in org.encog.neural.pattern: Pattern to create an ART-1 neural network.
ART1Pattern() - Constructor for class org.encog.neural.pattern.ART1Pattern
ARTLogic - Class in org.encog.neural.networks.logic: Base class for all forms of the adaptive resonance theory (ART) classes.
ARTLogic() - Constructor for class org.encog.neural.networks.logic.ARTLogic
assignID() - Method in class org.encog.neural.networks.structure.NeuralStructure: Assign an ID to every layer that does not already have one.
assignID(Layer) - Method in class org.encog.neural.networks.structure.NeuralStructure: Assign an ID to the specified layer.
ATTRIBUTE_CENTER - Static variable in class org.encog.persist.persistors.ActivationGaussianPersistor: THe center attribute.
ATTRIBUTE_DESCRIPTION - Static variable in class org.encog.persist.EncogPersistedCollection: The description attribute.
ATTRIBUTE_FROM - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The from attribute.
ATTRIBUTE_ID - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The id attribute.
ATTRIBUTE_LAYER - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The to attribute.
ATTRIBUTE_MATRIX_COLS - Static variable in class org.encog.persist.persistors.PersistorUtil: The columns in the matrix.
ATTRIBUTE_MATRIX_ROWS - Static variable in class org.encog.persist.persistors.PersistorUtil: The rows in the matrix.
ATTRIBUTE_NAME - Static variable in class org.encog.persist.EncogPersistedCollection: The name attribute.
ATTRIBUTE_NAME - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The name attribute.
ATTRIBUTE_NAME - Static variable in class org.encog.persist.persistors.PropertyDataPersistor: The name attribute.
ATTRIBUTE_NAME - Static variable in class org.encog.persist.persistors.TrainingContinuationPersistor: The name attribute.
ATTRIBUTE_NAME - Static variable in class org.encog.persist.PersistReader: The name attribute.
ATTRIBUTE_PEAK - Static variable in class org.encog.persist.persistors.ActivationGaussianPersistor: The peak attribute.
ATTRIBUTE_TO - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The to attribute.
ATTRIBUTE_TYPE - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The type attribute.
ATTRIBUTE_TYPE_BOTH - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The both layer type.
ATTRIBUTE_TYPE_HIDDEN - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The hidden layer type.
ATTRIBUTE_TYPE_INPUT - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The input layer type.
ATTRIBUTE_TYPE_OUTPUT - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The output layer type.
ATTRIBUTE_TYPE_UNKNOWN - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The unknown layer type.
ATTRIBUTE_VALUE - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The value attribute.
ATTRIBUTE_VALUE - Static variable in class org.encog.persist.persistors.PropertyDataPersistor: The value attribute.
ATTRIBUTE_WIDTH - Static variable in class org.encog.persist.persistors.ActivationGaussianPersistor: The width attribute.
ATTRIBUTE_WINNERS - Static variable in class org.encog.persist.persistors.ActivationCompetitivePersistor: The winners attribute.
autoDecay() - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining: Should be called each iteration if autodecay is desired.

B

Backpropagation - Class in org.encog.neural.networks.training.propagation.back: This class implements a backpropagation training algorithm for feed forward neural networks.
Backpropagation(BasicNetwork, NeuralDataSet) - Constructor for class org.encog.neural.networks.training.propagation.back.Backpropagation: Create a class to train using backpropagation.
Backpropagation(BasicNetwork, NeuralDataSet, double, double) - Constructor for class org.encog.neural.networks.training.propagation.back.Backpropagation
BAMLogic - Class in org.encog.neural.networks.logic: Provides the neural logic for an BAM type network.
BAMLogic() - Constructor for class org.encog.neural.networks.logic.BAMLogic
BAMPattern - Class in org.encog.neural.pattern: Construct a Bidirectional Access Memory (BAM) neural network.
BAMPattern() - Constructor for class org.encog.neural.pattern.BAMPattern
BasicActivationFunction - Class in org.encog.neural.activation: Holds basic functionality that all activation functions will likely have use of.
BasicActivationFunction() - Constructor for class org.encog.neural.activation.BasicActivationFunction
BasicInputField - Class in org.encog.normalize.input: Provides basic functionality, such as min/max and current value for other input fields.
BasicInputField() - Constructor for class org.encog.normalize.input.BasicInputField
BasicLayer - Class in org.encog.neural.networks.layers: Basic functionality that most of the neural layers require.
BasicLayer() - Constructor for class org.encog.neural.networks.layers.BasicLayer: Default constructor, mainly so the workbench can easily create a default layer.
BasicLayer(ActivationFunction, boolean, int) - Constructor for class org.encog.neural.networks.layers.BasicLayer: Construct this layer with a non-default threshold function.
BasicLayer(int) - Constructor for class org.encog.neural.networks.layers.BasicLayer: Construct this layer with a sigmoid threshold function.
BasicLayerPersistor - Class in org.encog.persist.persistors: Provides basic functions that many of the persistors will need.
BasicLayerPersistor() - Constructor for class org.encog.persist.persistors.BasicLayerPersistor
BasicNetwork - Class in org.encog.neural.networks: This class implements a neural network.
BasicNetwork() - Constructor for class org.encog.neural.networks.BasicNetwork: Construct an empty neural network.
BasicNetwork(NeuralLogic) - Constructor for class org.encog.neural.networks.BasicNetwork: Construct a basic network using the specified logic.
BasicNetworkPersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the BasicNetwork class.
BasicNetworkPersistor() - Constructor for class org.encog.persist.persistors.BasicNetworkPersistor
BasicNeuralData - Class in org.encog.neural.data.basic: Basic implementation of the NeuralData interface that stores the data in an array.
BasicNeuralData(double[]) - Constructor for class org.encog.neural.data.basic.BasicNeuralData: Construct this object with the specified data.
BasicNeuralData(int) - Constructor for class org.encog.neural.data.basic.BasicNeuralData: Construct this object with blank data and a specified size.
BasicNeuralData(NeuralData) - Constructor for class org.encog.neural.data.basic.BasicNeuralData: Construct a new BasicNeuralData object from an existing one.
BasicNeuralDataPair - Class in org.encog.neural.data.basic: A basic implementation of the NeuralDataPair interface.
BasicNeuralDataPair(NeuralData) - Constructor for class org.encog.neural.data.basic.BasicNeuralDataPair: Construct the object with only input.
BasicNeuralDataPair(NeuralData, NeuralData) - Constructor for class org.encog.neural.data.basic.BasicNeuralDataPair: Construct a BasicNeuralDataPair class with the specified input and ideal values.
BasicNeuralDataSet - Class in org.encog.neural.data.basic: neural data in an ArrayList.
BasicNeuralDataSet() - Constructor for class org.encog.neural.data.basic.BasicNeuralDataSet: Default constructor.
BasicNeuralDataSet(double[][], double[][]) - Constructor for class org.encog.neural.data.basic.BasicNeuralDataSet: Construct a data set from an input and idea array.
BasicNeuralDataSet(List<NeuralDataPair>) - Constructor for class org.encog.neural.data.basic.BasicNeuralDataSet: Construct a data set from an already created list.
BasicNeuralDataSet.BasicNeuralIterator - Class in org.encog.neural.data.basic: An iterator to be used with the BasicNeuralDataSet.
BasicNeuralDataSet.BasicNeuralIterator() - Constructor for class org.encog.neural.data.basic.BasicNeuralDataSet.BasicNeuralIterator
BasicNeuralDataSetPersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the ActivationBiPolar class.
BasicNeuralDataSetPersistor() - Constructor for class org.encog.persist.persistors.BasicNeuralDataSetPersistor
BasicOutputField - Class in org.encog.normalize.output: Provides very basic functionality for output fields.
BasicOutputField() - Constructor for class org.encog.normalize.output.BasicOutputField
BasicOutputFieldGroup - Class in org.encog.normalize.output: Provides very basic functionality that other output field groups will use.
BasicOutputFieldGroup() - Constructor for class org.encog.normalize.output.BasicOutputFieldGroup
BasicRandomizer - Class in org.encog.util.randomize: Provides basic functionality that most randomizers will need.
BasicRandomizer() - Constructor for class org.encog.util.randomize.BasicRandomizer
BasicSynapse - Class in org.encog.neural.networks.synapse: An abstract class that implements basic functionality that may be needed by the other synapse classes.
BasicSynapse() - Constructor for class org.encog.neural.networks.synapse.BasicSynapse
BasicTraining - Class in org.encog.neural.networks.training: An abstract class that implements basic training for most training algorithms.
BasicTraining() - Constructor for class org.encog.neural.networks.training.BasicTraining
begin() - Method in class org.encog.persist.PersistWriter: Begin an Encog document.
beginDocument() - Method in class org.encog.parse.tags.write.WriteTags: Called to begin the document.
beginEncogObject(String, WriteXML, EncogPersistedObject, boolean) - Static method in class org.encog.persist.persistors.PersistorUtil: Write the beginning XML for an Encog object.
beginLoad(int, int) - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet: Begin loading to the binary file.
beginObjects() - Method in class org.encog.persist.PersistWriter: Begin the objects collection.
beginRow() - Method in class org.encog.normalize.output.nominal.NominalItem: Begin a row.
beginScan(File) - Method in class org.encog.util.GenerateClasslist: Scan a directory.
beginTag(String) - Method in class org.encog.parse.tags.write.WriteTags: Begin a tag with the specified name.
BestMatchingUnit - Class in org.encog.neural.networks.training.competitive: The "Best Matching Unit" or BMU is a very important concept in the training for a SOM.
BestMatchingUnit(CompetitiveTraining) - Constructor for class org.encog.neural.networks.training.competitive.BestMatchingUnit: Construct a BestMatchingUnit class.
bipolar2double(boolean) - Static method in class org.encog.matrix.BiPolarUtil: Convert a boolean to a bipolar number.
bipolar2double(boolean[]) - Static method in class org.encog.matrix.BiPolarUtil: Convert a boolean array to a bipolar array.
bipolar2double(boolean[][]) - Static method in class org.encog.matrix.BiPolarUtil
BiPolarNeuralData - Class in org.encog.neural.data.bipolar: A NeuralData implementation designed to work with bipolar data.
BiPolarNeuralData(boolean[]) - Constructor for class org.encog.neural.data.bipolar.BiPolarNeuralData: Construct this object with the specified data.
BiPolarNeuralData(int) - Constructor for class org.encog.neural.data.bipolar.BiPolarNeuralData: Construct a data object with the specified size.
BiPolarUtil - Class in org.encog.matrix: This class contains a number of utility methods used to work with bipolar numbers.
BoltzmannLogic - Class in org.encog.neural.networks.logic: Provides the neural logic for an Boltzmann type network.
BoltzmannLogic() - Constructor for class org.encog.neural.networks.logic.BoltzmannLogic
BoltzmannPattern - Class in org.encog.neural.pattern: Pattern to create a Boltzmann machine.
BoltzmannPattern() - Constructor for class org.encog.neural.pattern.BoltzmannPattern
BotError - Exception in org.encog.bot: Used to represent any error that occurs in the bot part of Encog.
BotError(String) - Constructor for exception org.encog.bot.BotError: Construct a message exception.
BotError(Throwable) - Constructor for exception org.encog.bot.BotError: Construct an exception that holds another exception.
BotUtil - Class in org.encog.bot: Utility class for bots.
bound(double) - Static method in class org.encog.util.math.BoundNumbers: Bound the number so that it does not become too big or too small.
BoundMath - Class in org.encog.util.math: Java will sometimes return Math.NaN or Math.Infinity when numbers get to large or too small.
BoundNumbers - Class in org.encog.util.math: A simple class that prevents numbers from getting either too big or too small.
BrowseError - Exception in org.encog.bot.browse: Thrown when any sort of error related to web browsing is encountered.
BrowseError(String) - Constructor for exception org.encog.bot.browse.BrowseError: Construct a message exception.
BrowseError(Throwable) - Constructor for exception org.encog.bot.browse.BrowseError: Construct an exception that holds another exception.
Browser - Class in org.encog.bot.browse: The main class for web browsing.
Browser() - Constructor for class org.encog.bot.browse.Browser
BUFFER_SIZE - Static variable in class org.encog.bot.BotUtil: How much data to read at once.
BUFFER_SIZE - Static variable in class org.encog.util.file.Directory: Default buffer size for read/write operations.
BUFFER_SIZE - Static variable in class org.encog.util.http.FormUtility: The size of the read buffer.
BufferedNeuralDataSet - Class in org.encog.neural.data.buffer: This class is not memory based, so very long files can be used, without running out of memory.
BufferedNeuralDataSet(File) - Constructor for class org.encog.neural.data.buffer.BufferedNeuralDataSet: Construct a buffered dataset using the specified file.
BufferedNeuralDataSet.BufferedNeuralDataSetIterator - Class in org.encog.neural.data.buffer: An iterator to move through the buffered data set.
BufferedNeuralDataSet.BufferedNeuralDataSetIterator() - Constructor for class org.encog.neural.data.buffer.BufferedNeuralDataSet.BufferedNeuralDataSetIterator: Construct the buffered iterator.
buildDirectory() - Method in class org.encog.persist.EncogPersistedCollection: Build a directory of objects.
buildDirectory() - Method in class org.encog.persist.PersistReader: Build a directory entry list for the file.
buildForNetworkInput(double[]) - Method in class org.encog.normalize.DataNormalization: Build "input data for a neural network" based on the input values provided.

C

calculate(double[]) - Method in class org.encog.neural.networks.training.propagation.gradient.CalculateGradient: Calculate the gradients based on the specified weights.
calculate(NeuralData, NeuralData) - Method in class org.encog.neural.networks.training.propagation.gradient.GradientUtil: Calculate the gradents between the input and ideal data.
calculate(NeuralDataSet, double[]) - Method in class org.encog.neural.networks.training.propagation.gradient.GradientUtil: Calculate for an entire training set.
calculate(int) - Method in class org.encog.normalize.output.mapped.OutputFieldEncode: Calculate the value for this field.
calculate(int) - Method in class org.encog.normalize.output.multiplicative.OutputFieldMultiplicative: Calculate the value for this output field.
calculate(int) - Method in class org.encog.normalize.output.nominal.OutputEquilateral: Calculate the value for the specified subfield.
calculate(int) - Method in class org.encog.normalize.output.nominal.OutputOneOf: Calculate the value for the specified subfield.
calculate(int) - Method in interface org.encog.normalize.output.OutputField: Calculate the value for this field.
calculate(int) - Method in class org.encog.normalize.output.OutputFieldDirect: Calculate the value for this field.
calculate(double, double, double, double, double) - Static method in class org.encog.normalize.output.OutputFieldRangeMapped: Calculate a ranged mapped value.
calculate(int) - Method in class org.encog.normalize.output.OutputFieldRangeMapped: Calculate this output field.
calculate(int) - Method in class org.encog.normalize.output.zaxis.OutputFieldZAxis: Calculate the current value for this field.
calculate(int) - Method in class org.encog.normalize.output.zaxis.OutputFieldZAxisSynthetic: Calculate the synthetic value for this Z-Axis normalization.
calculate(double) - Method in class org.encog.util.math.rbf.GaussianFunction: Calculate the value of the Gaussian function for the specified value.
calculate(double[]) - Method in class org.encog.util.math.rbf.GaussianFunctionMulti: Calculate thre result from the function.
calculate(double) - Method in interface org.encog.util.math.rbf.RadialBasisFunction: Calculate the RBF result for the specified value.
calculate(double[]) - Method in interface org.encog.util.math.rbf.RadialBasisFunctionMulti: Calculate the RBF result for the specified value.
calculateActualSetSize() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Calculate the actual set size, this is the number of training set entries that will be generated.
calculateBMU(Synapse, NeuralData) - Method in class org.encog.neural.networks.training.competitive.BestMatchingUnit: Calculate the best matching unit (BMU).
CalculateDepth - Class in org.encog.neural.networks.structure: Utility class to calculate the depth that a layer is from the output layer.
CalculateDepth(BasicNetwork) - Constructor for class org.encog.neural.networks.structure.CalculateDepth: Construct the depth calculation object.
calculateDerivative(double) - Method in class org.encog.util.math.rbf.GaussianFunction: Calculate the value of the derivative of the Gaussian function for the specified value.
calculateDerivative(double) - Method in interface org.encog.util.math.rbf.RadialBasisFunction: Calculate the derivative of the RBF function.
calculateEnergy() - Method in class org.encog.neural.networks.logic.ThermalLogic
calculateError(NeuralDataSet) - Method in class org.encog.neural.networks.BasicNetwork: Calculate the error for this neural network.
calculateError(NeuralDataSet) - Method in interface org.encog.neural.networks.Network: Calculate the error for this neural network.
calculateEuclideanDistance(Synapse, NeuralData, int) - Method in class org.encog.neural.networks.training.competitive.BestMatchingUnit: Calculate the Euclidean distance for the specified output neuron and the input vector.
CalculateGradient - Class in org.encog.neural.networks.training.propagation.gradient: This class is used to calculate the gradients for each of the weights and thresholds values in a neural network.
CalculateGradient(BasicNetwork, NeuralDataSet) - Constructor for class org.encog.neural.networks.training.propagation.gradient.CalculateGradient: Construct the object using a network and training set.
CalculateGradient(BasicNetwork, NeuralDataSet, int) - Constructor for class org.encog.neural.networks.training.propagation.gradient.CalculateGradient: Construct the object for multithreaded use.
calculateNeuronCount() - Method in class org.encog.neural.networks.BasicNetwork: Calculate the total number of neurons in the network across all layers.
calculateNeuronCount() - Method in interface org.encog.neural.networks.Network: Calculate the total number of neurons in the network across all layers.
calculateNeuronCounts() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Calculate how many input and output neurons will be needed for the current data.
calculatePointsInRange() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Calculate how many points are in the high and low range.
calculateRMS() - Method in class org.encog.util.ErrorCalculation: Returns the root mean square error for a complete training set.
calculateScore() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealingHelper: Used to pass the determineError call on to the parent object.
CalculateScore - Interface in org.encog.neural.networks.training: Used by simulated annealing and genetic algorithms to calculate the score for a neural network.
calculateScore(BasicNetwork) - Method in interface org.encog.neural.networks.training.CalculateScore: Calculate this network's score.
calculateScore() - Method in class org.encog.neural.networks.training.genetic.NeuralChromosome: Calculate the score for this chromosome.
calculateScore(BasicNetwork) - Method in class org.encog.neural.networks.training.TrainingSetScore: Calculate the score for the network.
calculateScore() - Method in class org.encog.solve.anneal.SimulatedAnnealing: Subclasses should provide a method that evaluates the score for the current solution.
calculateScore() - Method in class org.encog.solve.genetic.Chromosome: Called to calculate the score for this chromosome.
calculateSize() - Method in class org.encog.neural.networks.structure.NeuralStructure: Calculate the size that an array should be to hold all of the weights and threshold values.
calculateStartIndex() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Calculate the index to start at.
canContinue() - Method in class org.encog.neural.networks.training.propagation.Propagation
canContinue() - Method in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation
CDATA_BEGIN - Static variable in class org.encog.parse.tags.TagConst: The beginning of a CDATA section.
CDATA_END - Static variable in class org.encog.parse.tags.TagConst: THe end of a CDATA section.
changeNeuronCount(Layer, int) - Method in class org.encog.neural.prune.PruneSelective: Change the neuron count for the network.
CHAR_BULLET - Static variable in class org.encog.parse.tags.read.ReadTags: The bullet character.
CHAR_TRADEMARK - Static variable in class org.encog.parse.tags.read.ReadTags: The bullet character.
CholeskyDecomposition - Class in org.encog.matrix.decomposition: Cholesky Decomposition.
CholeskyDecomposition(Matrix) - Constructor for class org.encog.matrix.decomposition.CholeskyDecomposition: Cholesky algorithm for symmetric and positive definite matrix.
Chromosome<GENE_TYPE> - Class in org.encog.solve.genetic: Implements a chromosome to genetic algorithm.
Chromosome() - Constructor for class org.encog.solve.genetic.Chromosome
clear() - Method in class org.encog.matrix.Matrix: Set all rows and columns to zero.
clear() - Method in class org.encog.neural.data.basic.BasicNeuralData: Set all data to zero.
clear() - Method in class org.encog.neural.data.bipolar.BiPolarNeuralData: Set all data to false.
clear() - Method in interface org.encog.neural.data.NeuralData: Clear any data to zero.
clear() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Clear the entire dataset.
clear() - Method in class org.encog.neural.networks.logic.BAMLogic: Clear any connection weights.
clear() - Method in class org.encog.neural.networks.logic.ThermalLogic: Clear any connection weights.
clear() - Method in class org.encog.neural.pattern.ADALINEPattern: Clear out any parameters.
clear() - Method in class org.encog.neural.pattern.ART1Pattern: Clear any properties set for this network.
clear() - Method in class org.encog.neural.pattern.BAMPattern: Clear any settings on the pattern.
clear() - Method in class org.encog.neural.pattern.BoltzmannPattern: Clear any properties set on this network.
clear() - Method in class org.encog.neural.pattern.CPNPattern: Clear any parameters that were set.
clear() - Method in class org.encog.neural.pattern.ElmanPattern: Clear out any hidden neurons.
clear() - Method in class org.encog.neural.pattern.FeedForwardPattern: Clear out any hidden neurons.
clear() - Method in class org.encog.neural.pattern.HopfieldPattern: Nothing to clear.
clear() - Method in class org.encog.neural.pattern.JordanPattern: Clear out any hidden neurons.
clear() - Method in interface org.encog.neural.pattern.NeuralNetworkPattern: Clear the hidden layers so that they can be redefined.
clear() - Method in class org.encog.neural.pattern.RadialBasisPattern: Clear out any hidden neurons.
clear() - Method in class org.encog.neural.pattern.RSOMPattern: Clear out any hidden neurons.
clear() - Method in class org.encog.neural.pattern.SOMPattern: Clear out any hidden neurons.
clear() - Method in class org.encog.parse.tags.Tag: Clear the name, type and attributes.
clear() - Method in class org.encog.persist.EncogPersistedCollection: Clear the collection.
clear() - Method in class org.encog.persist.persistors.generic.ObjectMapper: Clear the map and reference list.
clear() - Method in class org.encog.persist.persistors.generic.ObjectTagger: Clear the map and current id.
clearContext() - Method in class org.encog.neural.networks.BasicNetwork: Clear any data from any context layers.
clearContext() - Method in interface org.encog.neural.networks.ContextClearable: Clear the context for this layer.
clearContext() - Method in class org.encog.neural.networks.layers.ContextLayer: Reset the context values back to zero.
clearLayerTags() - Method in class org.encog.neural.networks.BasicNetwork: Remove all layer tags.
clone() - Method in class org.encog.matrix.Matrix: Create a copy of the matrix.
clone() - Method in class org.encog.neural.activation.ActivationBiPolar
clone() - Method in class org.encog.neural.activation.ActivationCompetitive
clone() - Method in class org.encog.neural.activation.ActivationGaussian
clone() - Method in class org.encog.neural.activation.ActivationLinear
clone() - Method in class org.encog.neural.activation.ActivationLOG
clone() - Method in class org.encog.neural.activation.ActivationSigmoid
clone() - Method in class org.encog.neural.activation.ActivationSIN
clone() - Method in class org.encog.neural.activation.ActivationSoftMax
clone() - Method in class org.encog.neural.activation.ActivationTANH
clone() - Method in class org.encog.neural.activation.BasicActivationFunction
clone() - Method in class org.encog.neural.data.basic.BasicNeuralData
clone() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet
clone() - Method in class org.encog.neural.data.bipolar.BiPolarNeuralData
clone() - Method in interface org.encog.neural.data.NeuralData: Clone this object.
clone() - Method in class org.encog.neural.data.PropertyData: Clone this object.
clone() - Method in class org.encog.neural.data.TextData: Clone this object.
clone() - Method in class org.encog.neural.networks.BasicNetwork: Return a clone of this neural network.
clone() - Method in interface org.encog.neural.networks.Network: Return a clone of this neural network.
clone() - Method in class org.encog.neural.networks.synapse.BasicSynapse
clone() - Method in class org.encog.neural.networks.synapse.DirectSynapse
clone() - Method in class org.encog.neural.networks.synapse.OneToOneSynapse
clone() - Method in interface org.encog.neural.networks.synapse.Synapse
clone() - Method in class org.encog.neural.networks.synapse.WeightedSynapse
clone() - Method in class org.encog.neural.networks.synapse.WeightlessSynapse
clone() - Method in class org.encog.parse.tags.Tag
close() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Close this data set.
close() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet.BufferedNeuralDataSetIterator: Close the iterator, and the underlying file.
close() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet: Close all iterators.
close() - Method in class org.encog.neural.data.csv.CSVNeuralDataSet: Close any iterators from this dataset.
close() - Method in class org.encog.neural.data.csv.CSVNeuralDataSet.CSVNeuralIterator: Close the iterator, and the underlying CSV file.
close() - Method in interface org.encog.neural.data.NeuralDataSet: Close this datasource and release any resources obtained by it, including any iterators created.
close() - Method in class org.encog.neural.data.sql.SQLNeuralDataSet: Close the SQL connection.
close() - Method in class org.encog.neural.data.sql.SQLNeuralDataSet.SQLNeuralIterator: Close this iterator and release any resources it had.
close() - Method in class org.encog.neural.data.union.UnionNeuralDataSet: Close the dataset.
close() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet: Close the XML data source.
close() - Method in interface org.encog.normalize.target.NormalizationStorage: Open the storage.
close() - Method in class org.encog.normalize.target.NormalizationStorageArray1D: Not needed for this storage type.
close() - Method in class org.encog.normalize.target.NormalizationStorageArray2D: Not needed for this storage type.
close() - Method in class org.encog.normalize.target.NormalizationStorageCSV: Close the CSV file.
close() - Method in class org.encog.normalize.target.NormalizationStorageNeuralDataSet: Not needed for this storage type.
close() - Method in class org.encog.parse.tags.write.WriteTags: Close this object.
close() - Method in class org.encog.persist.PersistReader: Close the file.
close() - Method in class org.encog.persist.PersistWriter: Close the writer.
close() - Method in class org.encog.util.csv.ReadCSV: Close the file.
code(TimeUnit) - Method in class org.encog.util.time.EnglishTimeUnitNames: Get the code for a TimeUnit.
code(TimeUnit) - Method in interface org.encog.util.time.TimeUnitNames: Get the code for the specified time unit.
CodeDataUnit - Class in org.encog.bot.dataunit: A data unit that holds code.
CodeDataUnit() - Constructor for class org.encog.bot.dataunit.CodeDataUnit
COMMENT_BEGIN - Static variable in class org.encog.parse.tags.TagConst: The beginning of a comment.
COMMENT_END - Static variable in class org.encog.parse.tags.TagConst: The end of a comment.
compare(Layer, Layer) - Method in class org.encog.neural.networks.structure.LayerComparator: Compare two layers.
compare(Synapse, Synapse) - Method in class org.encog.neural.networks.structure.SynapseComparator: Compare two layers.
compareTo(LoadedMarketData) - Method in class org.encog.neural.data.market.loader.LoadedMarketData: Allow market data to be sorted.
compareTo(TemporalPoint) - Method in class org.encog.neural.data.temporal.TemporalPoint: Compare two temporal points.
compareTo(Layer) - Method in class org.encog.neural.networks.layers.BasicLayer: Compare this layer to another.
compareTo(DirectoryEntry) - Method in class org.encog.persist.DirectoryEntry: Compare the two objects.
compareTo(Chromosome<GENE_TYPE>) - Method in class org.encog.solve.genetic.Chromosome: Used to compare two chromosomes.
CompetitiveTraining - Class in org.encog.neural.networks.training.competitive: This class implements competitive training, which would be used in a winner-take-all neural network, such as the self organizing map (SOM).
CompetitiveTraining(BasicNetwork, double, NeuralDataSet, NeighborhoodFunction) - Constructor for class org.encog.neural.networks.training.competitive.CompetitiveTraining: Create an instance of competitive training.
complete() - Method in class org.encog.util.http.FormUtility: Complete the building of the form.
compute(NeuralData) - Method in class org.encog.neural.networks.BasicNetwork: Compute the output for a given input to the neural network.
compute(NeuralData, NeuralOutputHolder) - Method in class org.encog.neural.networks.BasicNetwork: Compute the output for a given input to the neural network.
compute(NeuralData) - Method in class org.encog.neural.networks.layers.BasicLayer: Compute the outputs for this layer given the input pattern.
compute(NeuralData) - Method in interface org.encog.neural.networks.layers.Layer: Compute the output for this layer.
compute(NeuralData) - Method in class org.encog.neural.networks.layers.RadialBasisFunctionLayer: Compute the values before sending output to the next layer.
compute(BiPolarNeuralData, BiPolarNeuralData) - Method in class org.encog.neural.networks.logic.ART1Logic: Compute the output from the ART1 network.
compute(NeuralData, NeuralOutputHolder) - Method in class org.encog.neural.networks.logic.ART1Logic: Compute the output for the BasicNetwork class.
compute(NeuralData, NeuralOutputHolder) - Method in class org.encog.neural.networks.logic.BAMLogic: Setup the network logic, read parameters from the network.
compute(NeuralDataMapping) - Method in class org.encog.neural.networks.logic.BAMLogic: Compute the network for the specified input.
compute(NeuralData, NeuralOutputHolder) - Method in class org.encog.neural.networks.logic.BoltzmannLogic: Setup the network logic, read parameters from the network.
compute(NeuralData, NeuralOutputHolder) - Method in class org.encog.neural.networks.logic.FeedforwardLogic: Compute the output for a given input to the neural network.
compute(NeuralData, NeuralOutputHolder) - Method in interface org.encog.neural.networks.logic.NeuralLogic: Compute the output for the BasicNetwork class.
compute(NeuralData) - Method in interface org.encog.neural.networks.Network: Compute the output for a given input to the neural network.
compute(NeuralData, NeuralOutputHolder) - Method in interface org.encog.neural.networks.Network: Compute the output for a given input to the neural network.
compute(NeuralData) - Method in class org.encog.neural.networks.synapse.DirectSynapse: Compute the output from this synapse.
compute(NeuralData) - Method in class org.encog.neural.networks.synapse.OneToOneSynapse: Compute the output from this synapse.
compute(NeuralData) - Method in interface org.encog.neural.networks.synapse.Synapse: Compute the output from this synapse.
compute(NeuralData) - Method in class org.encog.neural.networks.synapse.WeightedSynapse: Compute the weighted output from this synapse.
compute(NeuralData) - Method in class org.encog.neural.networks.synapse.WeightlessSynapse: Compute the weightless output from this synapse.
ConcurrentJob - Class in org.encog.util.concurrency.job: This class forms the basis for a job that can be run concurrently.
ConcurrentJob(StatusReportable) - Constructor for class org.encog.util.concurrency.job.ConcurrentJob: Construct a concurrent job.
cond() - Method in class org.encog.matrix.decomposition.SingularValueDecomposition: Two norm condition number
ConsistentRandomizer - Class in org.encog.util.randomize: A randomizer that takes a seed and will always produce consistent results.
ConsistentRandomizer(double, double) - Constructor for class org.encog.util.randomize.ConsistentRandomizer: Construct a range randomizer.
ConsistentRandomizer(int, double, double) - Constructor for class org.encog.util.randomize.ConsistentRandomizer: Construct a range randomizer.
ConsoleStatusReportable - Class in org.encog: A simple status report that goes to the console.
ConsoleStatusReportable() - Constructor for class org.encog.ConsoleStatusReportable
ConstRandomizer - Class in org.encog.util.randomize: A randomizer that will create always set the random number to a const value, used mainly for testing.
ConstRandomizer(double) - Constructor for class org.encog.util.randomize.ConstRandomizer: Construct a range randomizer.
constructURL(URL, String, boolean) - Static method in class org.encog.util.http.URLUtility: Construct a URL from its basic parts.
containsInvalidURLCharacters(String) - Static method in class org.encog.util.http.URLUtility: Returns true if the URL contains any invalid characters.
containsLayerType(Class<?>) - Method in class org.encog.neural.networks.structure.NeuralStructure: Determine if the network contains a layer of the specified type.
ContextClearable - Interface in org.encog.neural.networks: Allows the clearContext method to be called.
ContextLayer - Class in org.encog.neural.networks.layers: Implements a context layer.
ContextLayer() - Constructor for class org.encog.neural.networks.layers.ContextLayer: Default constructor, mainly so the workbench can easily create a default layer.
ContextLayer(ActivationFunction, boolean, int) - Constructor for class org.encog.neural.networks.layers.ContextLayer: Construct a context layer with the parameters specified.
ContextLayer(int) - Constructor for class org.encog.neural.networks.layers.ContextLayer: Construct a default context layer that has the TANH activation function and the specified number of neurons.
ContextLayerPersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the ContextLayer class.
ContextLayerPersistor() - Constructor for class org.encog.persist.persistors.ContextLayerPersistor
Convert - Class in org.encog.util.math: This class is used to convert strings into numeric values.
convertBack(double) - Method in class org.encog.normalize.output.OutputFieldRangeMapped: Convert a number back after its been normalized.
convertCSV2Binary(File, File, int, int, boolean) - Static method in class org.encog.util.simple.EncogUtility: Convert a CSV file to a binary training file.
convertFilename(String, URL, boolean) - Static method in class org.encog.util.http.URLUtility: Convert a filename for local storage.
CookieUtility - Class in org.encog.util.http: This class allows URLConnection objects to process cookies.
CookieUtility() - Constructor for class org.encog.util.http.CookieUtility
copy(Matrix, Matrix) - Static method in class org.encog.matrix.MatrixMath: Copy from one matrix to another.
copy(NeuralDataMapping, NeuralDataMapping) - Static method in class org.encog.neural.networks.NeuralDataMapping: Copy from one object to the other.
copyFile(File, File) - Static method in class org.encog.util.file.Directory: Copy the specified file.
cos(double) - Static method in class org.encog.util.math.BoundMath: Calculate the cos.
CPNPattern - Class in org.encog.neural.pattern: Pattern that creates a CPN neural network.
CPNPattern() - Constructor for class org.encog.neural.pattern.CPNPattern
create() - Method in class org.encog.persist.EncogPersistedCollection: Create the file.
createColumnMatrix(double[]) - Static method in class org.encog.matrix.Matrix: Turn an array of doubles into a column matrix.
createDate(int, int, int) - Static method in class org.encog.util.time.DateUtil: Create a Date object with the specified date.
createInputStream() - Method in class org.encog.persist.location.FilePersistence
createInputStream() - Method in class org.encog.persist.location.InputStreamPersistence: Create the input stream.
createInputStream() - Method in class org.encog.persist.location.OutputStreamPersistence: Can't create an InputStream for this object type, throw an error.
createInputStream() - Method in interface org.encog.persist.location.PersistenceLocation
createInputStream() - Method in class org.encog.persist.location.ResourcePersistence: Create an input stream to read from the resource.
createOutputStream() - Method in class org.encog.persist.location.FilePersistence
createOutputStream() - Method in class org.encog.persist.location.InputStreamPersistence: Try to create an output stream.
createOutputStream() - Method in class org.encog.persist.location.OutputStreamPersistence: Provide the output stream to use.
createOutputStream() - Method in interface org.encog.persist.location.PersistenceLocation
createOutputStream() - Method in class org.encog.persist.location.ResourcePersistence: Write operations are not supported for resource persistence.
createPair() - Method in class org.encog.neural.networks.training.propagation.gradient.CalculateGradient: Create a new neural data pair object of the correct size for the neural network that is being trained.
createPersistor() - Method in class org.encog.matrix.Matrix: Create a Persistor for this object.
createPersistor() - Method in class org.encog.neural.activation.ActivationBiPolar: Create a Persistor for this activation function.
createPersistor() - Method in class org.encog.neural.activation.ActivationCompetitive
createPersistor() - Method in class org.encog.neural.activation.ActivationGaussian: Create a Persistor for this activation function.
createPersistor() - Method in class org.encog.neural.activation.ActivationLinear: Create a Persistor for this activation function.
createPersistor() - Method in class org.encog.neural.activation.ActivationLOG: Create a Persistor for this activation function.
createPersistor() - Method in class org.encog.neural.activation.ActivationSigmoid: Create a Persistor for this activation function.
createPersistor() - Method in class org.encog.neural.activation.ActivationSIN: Create a Persistor for this activation function.
createPersistor() - Method in class org.encog.neural.activation.ActivationSoftMax: Create a Persistor for this activation function.
createPersistor() - Method in class org.encog.neural.activation.ActivationTANH: Create a Persistor for this activation function.
createPersistor() - Method in class org.encog.neural.activation.BasicActivationFunction: Create a Persistor for this activation function.
createPersistor() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Create a persistor for this object.
createPersistor() - Method in class org.encog.neural.data.PropertyData
createPersistor() - Method in class org.encog.neural.data.TextData: Create a persistor to store this object.
createPersistor() - Method in class org.encog.neural.networks.BasicNetwork: Create a persistor for this object.
createPersistor() - Method in class org.encog.neural.networks.layers.BasicLayer: Create a persistor for this layer.
createPersistor() - Method in class org.encog.neural.networks.layers.ContextLayer: Create a persistor for this layer.
createPersistor() - Method in class org.encog.neural.networks.layers.RadialBasisFunctionLayer: Create a persistor for this layer.
createPersistor() - Method in interface org.encog.neural.networks.Network: Create a persistor for this object.
createPersistor() - Method in class org.encog.neural.networks.synapse.DirectSynapse: Create a persistor for this type of synapse.
createPersistor() - Method in class org.encog.neural.networks.synapse.OneToOneSynapse
createPersistor() - Method in class org.encog.neural.networks.synapse.WeightedSynapse: Return a persistor for this object.
createPersistor() - Method in class org.encog.neural.networks.synapse.WeightlessSynapse: Return a persistor for this object.
createPersistor() - Method in class org.encog.neural.networks.training.propagation.TrainingContinuation
createPersistor() - Method in class org.encog.normalize.DataNormalization
createPersistor() - Method in interface org.encog.persist.EncogPersistedObject: Create a persistor for this object.
createPersistor(String) - Static method in class org.encog.persist.persistors.PersistorUtil: Create a persistor object.
createPoint(Date) - Method in class org.encog.neural.data.market.MarketNeuralDataSet: Create a datapoint at the specified date.
createPoint(Date) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Create a temporal point from a time.
createPoint(int) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Create a temporal data point using a sequence number.
createRowMatrix(double[]) - Static method in class org.encog.matrix.Matrix: Turn an array of doubles into a row matrix.
CSVError - Exception in org.encog.util.csv: An error has occured while working with CSV data.
CSVError(String) - Constructor for exception org.encog.util.csv.CSVError: Construct a message exception.
CSVError(Throwable) - Constructor for exception org.encog.util.csv.CSVError: Construct an exception that holds another exception.
CSVFormat - Class in org.encog.util.csv: Specifies a CSV format.
CSVFormat() - Constructor for class org.encog.util.csv.CSVFormat: By default use USA conventions.
CSVFormat(char, char) - Constructor for class org.encog.util.csv.CSVFormat: Construct a CSV format with he specified decimal and separator characters.
CSVNeuralDataSet - Class in org.encog.neural.data.csv: An implementation of the NeuralDataSet interface designed to provide a CSV file to the neural network.
CSVNeuralDataSet(String, int, int, boolean) - Constructor for class org.encog.neural.data.csv.CSVNeuralDataSet: Construct this data set using a comma as a delimiter.
CSVNeuralDataSet(String, int, int, boolean, CSVFormat) - Constructor for class org.encog.neural.data.csv.CSVNeuralDataSet: Construct this data set using a comma as a delimiter.
CSVNeuralDataSet.CSVNeuralIterator - Class in org.encog.neural.data.csv: An iterator designed to read from CSV files.
CSVNeuralDataSet.CSVNeuralIterator() - Constructor for class org.encog.neural.data.csv.CSVNeuralDataSet.CSVNeuralIterator: Default constructor.
CUT - Static variable in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing: The cutoff for random data.

D

DataNormalization - Class in org.encog.normalize: This class is used to normalize both input and ideal data for neural networks.
DataNormalization() - Constructor for class org.encog.normalize.DataNormalization
DataUnit - Class in org.encog.bot.dataunit: Data units are very abstract pieces of data that the browser processes.
DataUnit() - Constructor for class org.encog.bot.dataunit.DataUnit
DateUtil - Class in org.encog.util.time: Simple date utility class.
DAYS_WEEK - Static variable in class org.encog.util.time.TimeSpan: Days in a week.
decay(double) - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining: Called to decay the learning rate and radius by the specified amount.
decay(double, double) - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining: Decay the learning rate and radius by the specified amount.
DECIMAL_COMMA - Static variable in class org.encog.util.csv.CSVFormat: Use a decimal comma, and a semicolon to separate numbers.
DECIMAL_POINT - Static variable in class org.encog.util.csv.CSVFormat: Use a decimal point, and a comma to separate numbers.
decode(double[]) - Method in class org.encog.util.math.Equilateral: Decode a set of activations and see which set it has the lowest Euclidean distance from.
decreaseTemperature(double) - Method in class org.encog.neural.networks.logic.BoltzmannLogic: Decrease the temperature by the specified amount.
deepCopy(Object) - Static method in class org.encog.util.ObjectCloner: Perform a deep copy.
DEFAULT_ALTERNATE_CYCLES - Static variable in class org.encog.neural.networks.training.strategy.HybridStrategy: The default number of cycles to use the alternate training for.
DEFAULT_INITIAL_UPDATE - Static variable in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation: The starting update for a delta.
DEFAULT_MAX_STEP - Static variable in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation: The maximum amount a delta can reach.
DEFAULT_MIN_IMPROVEMENT - Static variable in class org.encog.neural.networks.training.strategy.HybridStrategy: The default minimum improvement before we switch to the alternate training method.
DEFAULT_MIN_IMPROVEMENT - Static variable in class org.encog.neural.networks.training.strategy.StopTrainingStrategy: The default minimum improvement before training stops.
DEFAULT_PRECISION - Static variable in class org.encog.Encog: The default precision to use for compares.
DEFAULT_TOLERATE_CYCLES - Static variable in class org.encog.neural.networks.training.strategy.HybridStrategy: The default number of cycles to tolerate bad improvement for.
DEFAULT_TOLERATE_CYCLES - Static variable in class org.encog.neural.networks.training.strategy.StopTrainingStrategy: The default number of cycles to tolerate.
DEFAULT_ZERO_TOLERANCE - Static variable in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation: The default zero tolerance.
defineCutLength() - Method in class org.encog.solve.genetic.GeneticAlgorithm: Define the cut length to be 1/3 the length of a chromosome.
delete(DirectoryEntry) - Method in class org.encog.persist.EncogPersistedCollection: Delete the specified object, use a directory entry.
delete(EncogPersistedObject) - Method in class org.encog.persist.EncogPersistedCollection: Delete the specified object.
delete(String) - Method in class org.encog.persist.EncogPersistedCollection: Delete the specified object.
delete() - Method in class org.encog.persist.location.FilePersistence: Attempt to delete the file.
delete() - Method in class org.encog.persist.location.InputStreamPersistence: Delete operations are not supported for resource persistence.
delete() - Method in class org.encog.persist.location.OutputStreamPersistence: Delete operations are not supported for resource persistence.
delete() - Method in interface org.encog.persist.location.PersistenceLocation: Delete the location, if possible.
delete() - Method in class org.encog.persist.location.ResourcePersistence: Delete operations are not supported for resource persistence.
deleteCol(Matrix, int) - Static method in class org.encog.matrix.MatrixMath: Delete one column from the matrix.
deleteDirectory(File) - Static method in class org.encog.util.file.Directory: Delete a directory and all children.
deleteRow(Matrix, int) - Static method in class org.encog.matrix.MatrixMath: Delete a row from the matrix.
DELTA_MIN - Static variable in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation: The minimum delta value for a weight matrix value.
derivativeFunction(double[]) - Method in class org.encog.neural.activation.ActivationBiPolar: Implements the activation function derivative.
derivativeFunction(double[]) - Method in class org.encog.neural.activation.ActivationCompetitive: Implements the activation function.
derivativeFunction(double[]) - Method in interface org.encog.neural.activation.ActivationFunction: Implements the activation function derivative.
derivativeFunction(double[]) - Method in class org.encog.neural.activation.ActivationGaussian: Implements the activation function derivative.
derivativeFunction(double[]) - Method in class org.encog.neural.activation.ActivationLinear: Implements the activation function derivative.
derivativeFunction(double[]) - Method in class org.encog.neural.activation.ActivationLOG: Implements the activation function derivative.
derivativeFunction(double[]) - Method in class org.encog.neural.activation.ActivationSigmoid: Implements the activation function derivative.
derivativeFunction(double[]) - Method in class org.encog.neural.activation.ActivationSIN: Implements the activation function derivative.
derivativeFunction(double[]) - Method in class org.encog.neural.activation.ActivationSoftMax: Implements the activation function derivative.
derivativeFunction(double[]) - Method in class org.encog.neural.activation.ActivationTANH: Implements the activation function derivative.
det() - Method in class org.encog.matrix.decomposition.LUDecomposition: Determinant
determineNeuronSignificance(Layer, int) - Method in class org.encog.neural.prune.PruneSelective: Determine the significance of the neuron.
determineWinner(NeuralData) - Static method in class org.encog.neural.networks.BasicNetwork: Determine which member of the output is the winning neuron.
Directory - Class in org.encog.util.file: Directory utilities.
DirectoryEntry - Class in org.encog.persist: The idea of the Encog persisted collection is that the entire file might be quite long and should not be read into memory in its entirity.
DirectoryEntry(EncogPersistedObject) - Constructor for class org.encog.persist.DirectoryEntry: Construct a directory entry for the specified object.
DirectoryEntry(String, String, String) - Constructor for class org.encog.persist.DirectoryEntry: Construct a directory entry from strings.
DirectSynapse - Class in org.encog.neural.networks.synapse: A direct synapse will present the entire input array to each of the directly connected neurons in the next layer.
DirectSynapse() - Constructor for class org.encog.neural.networks.synapse.DirectSynapse: Simple default constructor.
DirectSynapse(Layer, Layer) - Constructor for class org.encog.neural.networks.synapse.DirectSynapse: Construct a direct synapse between the two specified layers.
DirectSynapsePersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the DirectSynapse class.
DirectSynapsePersistor() - Constructor for class org.encog.persist.persistors.DirectSynapsePersistor
displayDate(Date) - Static method in class org.encog.util.csv.ReadCSV: Format a date.
Distort - Class in org.encog.util.randomize: A randomizer that distorts what is already present in the neural network.
Distort(double) - Constructor for class org.encog.util.randomize.Distort: Construct a distort randomizer for the specified factor.
DISTORT_FACTOR - Static variable in class org.encog.neural.networks.training.genetic.NeuralChromosome: The amount of distortion to perform a mutation.
Div - Class in org.encog.bot.browse.range: A document range that represents the beginning and ending DIV tag, as well as any tages embedded between them.
Div(WebPage) - Constructor for class org.encog.bot.browse.range.Div: Construct a range to hold the DIV tag.
divide(Matrix, double) - Static method in class org.encog.matrix.MatrixMath: Return a matrix with each cell divided by the specified value.
DocumentRange - Class in org.encog.bot.browse.range: Base class that represents a document range.
DocumentRange(WebPage) - Constructor for class org.encog.bot.browse.range.DocumentRange: Construct a document range from the specified WebPage.
dotProduct(Matrix, Matrix) - Static method in class org.encog.matrix.MatrixMath: Compute the dot product for the two matrixes.
double2bipolar(double) - Static method in class org.encog.matrix.BiPolarUtil: Convert a bipolar value to a boolean.
double2bipolar(double[]) - Static method in class org.encog.matrix.BiPolarUtil: Convert a bipolar array to booleans.
double2bipolar(double[][]) - Static method in class org.encog.matrix.BiPolarUtil: Convert a bipolar array to a boolean array.
doubleToObject(double[]) - Static method in class org.encog.util.EncogArray: Convert an array of double primitives to Double objects.
downsample(Downsample, boolean, int, int, double, double) - Method in class org.encog.neural.data.image.ImageNeuralData: Downsample, and copy, the image contents into the data of this object.
downsample(int, int) - Method in class org.encog.neural.data.image.ImageNeuralDataSet: Downsample all images and generate training data.
Downsample - Interface in org.encog.util.downsample: Utility to downsample an image.
downSample(Image, int, int) - Method in interface org.encog.util.downsample.Downsample: Downsample the image to the specified height and width.
downSample(Image, int, int) - Method in class org.encog.util.downsample.RGBDownsample: Called to downsample the image and store it in the down sample component.
downSample(Image, int, int) - Method in class org.encog.util.downsample.SimpleIntensityDownsample: Called to downsample the image and store it in the down sample component.
downSampleRegion(int, int) - Method in class org.encog.util.downsample.RGBDownsample: Called to downsample a region of the image.
dumpArray(double[]) - Static method in class org.encog.util.logging.DumpMatrix: Dump an array of numbers to a string.
dumpCounts() - Method in class org.encog.normalize.segregate.IntegerBalanceSegregator
DumpMatrix - Class in org.encog.util.logging: A utility for writing matrixes to the log.
dumpMatrix(Matrix) - Static method in class org.encog.util.logging.DumpMatrix: Dump a matrix to a string.

E

eatWhitespace() - Method in class org.encog.parse.tags.read.ReadTags: Remove any whitespace characters that are next in the InputStream.
EG_FORMAT - Static variable in class org.encog.util.csv.CSVFormat: EG files, internally use a decimal point and comma separator.
EGAttribute - Annotation Type in org.encog.persist.annotations: This annotation is used with Encog generic persistence.
EGIgnore - Annotation Type in org.encog.persist.annotations: This annotation is used with Encog generic persistence.
EGReference - Annotation Type in org.encog.persist.annotations: This annotation is used with Encog generic persistence.
EGReferenceable - Annotation Type in org.encog.persist.annotations: This annotation is used with Encog generic persistence.
EGUnsupported - Annotation Type in org.encog.persist.annotations: This annotation is used with Encog generic persistence.
EigenvalueDecomposition - Class in org.encog.matrix.decomposition: Eigenvalues and eigenvectors of a real matrix.
EigenvalueDecomposition(Matrix) - Constructor for class org.encog.matrix.decomposition.EigenvalueDecomposition: Check for symmetry, then construct the eigenvalue decomposition
ElmanPattern - Class in org.encog.neural.pattern: This class is used to generate an Elman style recurrent neural network.
ElmanPattern() - Constructor for class org.encog.neural.pattern.ElmanPattern: Create an object to generate Elman neural networks.
ENCODE - Static variable in class org.encog.util.http.FormUtility: The charset to use for URL encoding.
encode(int) - Method in class org.encog.util.math.Equilateral: Get the activations for the specified set.
Encog - Class in org.encog: Main Encog class, does little more than provide version information.
ENCOG_FILE_VERSION - Static variable in class org.encog.Encog: The encog file version.
ENCOG_VERSION - Static variable in class org.encog.Encog: The version of the Encog JAR we are working with.
EncogArray - Class in org.encog.util: Some array functions used by Encog.
EncogBenchmark - Class in org.encog.util.benchmark: Benchmark Encog with several network types.
EncogBenchmark(StatusReportable) - Constructor for class org.encog.util.benchmark.EncogBenchmark: Construct a benchmark object.
EncogConcurrency - Class in org.encog.util.concurrency: This class abstracts thread pools, and potentially grids and other types of concurrency.
EncogConcurrency() - Constructor for class org.encog.util.concurrency.EncogConcurrency: Construct a concurrency object.
EncogError - Exception in org.encog: General error class for Encog.
EncogError(String) - Constructor for exception org.encog.EncogError: Construct a message exception.
EncogError(Throwable) - Constructor for exception org.encog.EncogError: Construct an exception that holds another exception.
EncogError(String, Throwable) - Constructor for exception org.encog.EncogError: Construct an exception that holds another exception.
EncogFormatter - Class in org.encog.util.logging: A simple formatter for logging.
EncogFormatter() - Constructor for class org.encog.util.logging.EncogFormatter
EncogMath - Class in org.encog.util.math
EncogMath() - Constructor for class org.encog.util.math.EncogMath
EncogMemoryCollection - Class in org.encog.persist: A memory based collection of Encog objects.
EncogMemoryCollection() - Constructor for class org.encog.persist.EncogMemoryCollection
EncogPersistedCollection - Class in org.encog.persist: An EncogPersistedCollection holds a collection of EncogPersistedObjects.
EncogPersistedCollection(File) - Constructor for class org.encog.persist.EncogPersistedCollection: Create a persistance collection for the specified file.
EncogPersistedCollection(PersistenceLocation) - Constructor for class org.encog.persist.EncogPersistedCollection: Create an object based on the specified location.
EncogPersistedCollection(String) - Constructor for class org.encog.persist.EncogPersistedCollection: Construct an object with the specified filename.
EncogPersistedObject - Interface in org.encog.persist: This interface flags an class as being able to be persisted into an Encog collection.
EncogTask - Interface in org.encog.util.concurrency: An individual task that can be submitted to the EncogCurrency utility.
EncogUtility - Class in org.encog.util.simple: General utility class for Encog.
EncogValidate - Class in org.encog.util
EncogValidate() - Constructor for class org.encog.util.EncogValidate
end() - Method in class org.encog.persist.PersistWriter: End the document.
endDocument() - Method in class org.encog.parse.tags.write.WriteTags: End the document.
endLoad() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet: This method should be called once all the data has been loaded.
endObjects() - Method in class org.encog.persist.PersistWriter: End the objects collection.
endTag() - Method in class org.encog.parse.tags.write.WriteTags: End the current tag.
endTag(String) - Method in class org.encog.parse.tags.write.WriteTags: End a tag, require that we are ending the specified tag.
ENGLISH - Static variable in class org.encog.util.csv.CSVFormat: Decimal point is typically used in English speaking counties.
EnglishTimeUnitNames - Class in org.encog.util.time: Class used to get the English names for TimeUnits.
EnglishTimeUnitNames() - Constructor for class org.encog.util.time.EnglishTimeUnitNames
equal(Layer, Layer) - Method in class org.encog.neural.networks.structure.LayerComparator: Determine if two layers are equal.
equals(Object) - Method in class org.encog.matrix.Matrix: Check to see if this matrix equals another, using default precision.
equals(Matrix, int) - Method in class org.encog.matrix.Matrix: Compare to matrixes with the specified level of precision.
equals(TickerSymbol) - Method in class org.encog.neural.data.market.TickerSymbol: Determine if two ticker symbols equal each other.
equals(BasicNetwork) - Method in class org.encog.neural.networks.BasicNetwork: Compare the two neural networks.
equals(BasicNetwork, int) - Method in class org.encog.neural.networks.BasicNetwork: Determine if this neural network is equal to another.
equals(BasicNetwork) - Method in interface org.encog.neural.networks.Network: Compare the two neural networks.
equals(BasicNetwork, int) - Method in interface org.encog.neural.networks.Network: Determine if this neural network is equal to another.
equals(BasicNetwork, BasicNetwork, int) - Static method in class org.encog.neural.networks.structure.NetworkCODEC: Determine if the two neural networks are equal.
equals(Object) - Method in class org.encog.persist.DirectoryEntry: Returns true if the two objects are equal.
Equilateral - Class in org.encog.util.math: Used to produce an array of activations to classify data into groups.
Equilateral(int, double, double) - Constructor for class org.encog.util.math.Equilateral: Construct an equilateral matrix.
ERROR_ADD - Static variable in class org.encog.neural.data.buffer.BufferedNeuralDataSet: Error message for ADD.
ERROR_REMOVE - Static variable in class org.encog.neural.data.buffer.BufferedNeuralDataSet: Error message for REMOVE.
ErrorCalculation - Class in org.encog.util: An implementation of root mean square (RMS) error calculation.
ErrorCalculation() - Constructor for class org.encog.util.ErrorCalculation
establishEquilibrium() - Method in class org.encog.neural.networks.logic.BoltzmannLogic: Run the network until thermal equilibrium is established.
EULERS_NUMBER - Static variable in class org.encog.util.math.MathConst: Euler's number.
Evaluate - Class in org.encog.util.benchmark: Used to evaluate the training time for a network.
evaluate(BasicNetwork, NeuralDataSet) - Static method in class org.encog.util.simple.EncogUtility: Evaluate the network and display (to the console) the output for every value in the training set.
evaluateNetwork(BasicNetwork, NeuralDataSet) - Static method in class org.encog.util.benchmark.Evaluate: Evaluate how long it takes to calculate the error for the network.
evaluateTrain(BasicNetwork, NeuralDataSet) - Static method in class org.encog.util.benchmark.Evaluate: Evaluate how long it takes to calculate the error for the network.
exists() - Method in class org.encog.persist.location.FilePersistence
exists() - Method in class org.encog.persist.location.InputStreamPersistence: Because this is based on a stream, it always exists, so return true.
exists() - Method in class org.encog.persist.location.OutputStreamPersistence
exists() - Method in interface org.encog.persist.location.PersistenceLocation
exists() - Method in class org.encog.persist.location.ResourcePersistence: Exist is not supported for resource persistence.
exp(double) - Static method in class org.encog.util.math.BoundMath: Calculate the exp.
extract(String, String, String, int) - Static method in class org.encog.bot.BotUtil: This method is very useful for grabbing information from a HTML page.
extractFromIndex(String, String, String, int, int) - Static method in class org.encog.bot.BotUtil: This method is very useful for grabbing information from a HTML page.

F

FanInRandomizer - Class in org.encog.util.randomize: A randomizer that attempts to create starting weight values that are conducive to back propagation training.
FanInRandomizer() - Constructor for class org.encog.util.randomize.FanInRandomizer: Create a fan-in randomizer with default values.
FanInRandomizer(double, boolean) - Constructor for class org.encog.util.randomize.FanInRandomizer: Construct a fan-in randomizer along the specified boundary.
FanInRandomizer(double, double, boolean) - Constructor for class org.encog.util.randomize.FanInRandomizer: Construct a fan-in randomizer.
FeedforwardLogic - Class in org.encog.neural.networks.logic: Provides the neural logic for an Feedforward type network.
FeedforwardLogic() - Constructor for class org.encog.neural.networks.logic.FeedforwardLogic
FeedForwardPattern - Class in org.encog.neural.pattern: Used to create feedforward neural networks.
FeedForwardPattern() - Constructor for class org.encog.neural.pattern.FeedForwardPattern
FieldMapping - Class in org.encog.persist.persistors.generic: A simple mapping that holds the reference, field and target of an object.
FieldMapping(int, Field, Object) - Constructor for class org.encog.persist.persistors.generic.FieldMapping: Construct a field mapping.
FilePersistence - Class in org.encog.persist.location: A persistence location based on a file.
FilePersistence(File) - Constructor for class org.encog.persist.location.FilePersistence: Construct a persistance location based on a file.
finalizeStructure() - Method in class org.encog.neural.networks.structure.NeuralStructure: Build the synapse and layer structure.
find(Class<?>, int) - Method in class org.encog.bot.browse.WebPage: Find the specified DocumentRange subclass in the contents list.
find(DirectoryEntry) - Method in class org.encog.persist.EncogPersistedCollection: Find the specified object, using a DirectoryEntry.
find(String) - Method in class org.encog.persist.EncogPersistedCollection: Called to search all Encog objects in this collection for one with a name that passes what was passed in.
findBounds() - Method in interface org.encog.util.downsample.Downsample: Find the bounds around the image to exclude whitespace.
findBounds() - Method in class org.encog.util.downsample.RGBDownsample: This method is called to automatically crop the image so that whitespace is removed.
FindCPN - Class in org.encog.neural.networks.training.cpn: Find the parts of a CPN network.
FindCPN(BasicNetwork) - Constructor for class org.encog.neural.networks.training.cpn.FindCPN: Construct the object and find the parts of the network.
findEndTag(int, Tag) - Method in class org.encog.bot.browse.LoadWebPage: Find the end tag that lines up to the beginning tag.
findField(Class<?>, String) - Static method in class org.encog.util.ReflectionUtil: Find the specified field, look also in superclasses.
findInputField(Class<?>, int) - Method in class org.encog.normalize.DataNormalization: Find an input field by its class.
findLink(String) - Method in class org.encog.bot.browse.WebPage: Find the link that contains the specified string.
findOccurance(String, String, int) - Static method in class org.encog.bot.BotUtil: Find the specified occurrence of one string in another string.
findOutputField(Class<?>, int) - Method in class org.encog.normalize.DataNormalization: Find an output field by its class.
findSynapse(Layer, Layer, boolean) - Method in class org.encog.neural.networks.structure.NeuralStructure: Find the specified synapse, throw an error if it is required.
findTag(String, boolean) - Method in class org.encog.parse.tags.read.ReadXML: Advance until the specified tag is found.
findType(String, int) - Method in class org.encog.bot.browse.range.Form: Find the form input by type.
finishTraining() - Method in class org.encog.neural.networks.training.BasicTraining: Should be called after training has completed and the iteration method will not be called any further.
finishTraining() - Method in interface org.encog.neural.networks.training.Train: Should be called once training is complete and no more iterations are needed.
FIRST_LAMBDA - Static variable in class org.encog.neural.networks.training.propagation.scg.ScaledConjugateGradient: The starting value for lambda.
FIRST_SIGMA - Static variable in class org.encog.neural.networks.training.propagation.scg.ScaledConjugateGradient: The starting value for sigma.
Form - Class in org.encog.bot.browse.range: A document range that represents a form, and all embedded tags.
Form(WebPage) - Constructor for class org.encog.bot.browse.range.Form: Construct a form on the specified web page.
Form.Method - Enum in org.encog.bot.browse.range: The method for this form.
format(double, int) - Method in class org.encog.util.csv.CSVFormat: Format the specified number to a string with the specified number of fractional digits.
Format - Class in org.encog.util: Provides the ability for Encog to format numbers and times.
format(LogRecord) - Method in class org.encog.util.logging.EncogFormatter: Format the log record.
formatDouble(double, int) - Static method in class org.encog.util.Format: Format a double.
formatInteger(int) - Static method in class org.encog.util.Format: Format an integer.
formatPercent(double) - Static method in class org.encog.util.Format: Format a percent.
formatPercentWhole(double) - Static method in class org.encog.util.Format: Format a percent with no decimal places.
formatTimeSpan(int) - Static method in class org.encog.util.Format: Format a time span as seconds, minutes, hours and days.
FormElement - Class in org.encog.bot.browse.range: A document range that represents one individual component to a form.
FormElement(WebPage) - Constructor for class org.encog.bot.browse.range.FormElement: Construct a form element from the specified web page.
FormUtility - Class in org.encog.util.http: This class is used to construct responses to HTML forms.
FormUtility(OutputStream, String) - Constructor for class org.encog.util.http.FormUtility: Prepare to access either a regular, or multipart, form.
fromArray(double[]) - Static method in class org.encog.neural.activation.ActivationUtil: Get a single value from an array.
fromList(CSVFormat, String) - Static method in class org.encog.util.csv.NumberList: Get an array of double's from a string of comma separated text.
fromPackedArray(Double[], int) - Method in class org.encog.matrix.Matrix: Create a matrix from a packed array.
function(int, int) - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodBubble: Determine how much the current neuron should be affected by training based on its proximity to the winning neuron.
function(int, int) - Method in interface org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodFunction: Determine how much the current neuron should be affected by training based on its proximity to the winning neuron.
function(int, int) - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodGaussian: Determine how much the current neuron should be affected by training based on its proximity to the winning neuron.
function(int, int) - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodGaussianMulti: Calculate the value for the multi RBF function.
function(int, int) - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodSingle: Determine how much the current neuron should be affected by training based on its proximity to the winning neuron.

G

GaussianFunction - Class in org.encog.util.math.rbf: Implements a radial function based on the gaussian function.
GaussianFunction(double, double, double) - Constructor for class org.encog.util.math.rbf.GaussianFunction: Construct a Gaussian RBF with the specified center, peak and width.
GaussianFunctionMulti - Class in org.encog.util.math.rbf: Multi-dimensional gaussian function.
GaussianFunctionMulti(double, double[], double[]) - Constructor for class org.encog.util.math.rbf.GaussianFunctionMulti: Construct a multi-dimension Gaussian function with the specified peak, centers and widths.
GaussianFunctionMulti(int, double, double, double) - Constructor for class org.encog.util.math.rbf.GaussianFunctionMulti: Construct a Gaussian function with the specified number of dimensions.
GENERAL_ERROR - Static variable in class org.encog.persist.EncogPersistedCollection: Generic error message for bad XML.
generate() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Generate the training sets.
generate() - Method in class org.encog.neural.pattern.ADALINEPattern: Generate the network.
generate() - Method in class org.encog.neural.pattern.ART1Pattern: Generate the neural network.
generate() - Method in class org.encog.neural.pattern.BAMPattern
generate() - Method in class org.encog.neural.pattern.BoltzmannPattern: Generate the network.
generate() - Method in class org.encog.neural.pattern.CPNPattern: Generate the network.
generate() - Method in class org.encog.neural.pattern.ElmanPattern: Generate the Elman neural network.
generate() - Method in class org.encog.neural.pattern.FeedForwardPattern: Generate the Elman neural network.
generate() - Method in class org.encog.neural.pattern.HopfieldPattern: Generate the Hopfield neural network.
generate() - Method in class org.encog.neural.pattern.JordanPattern: Generate a Jordan neural network.
generate() - Method in interface org.encog.neural.pattern.NeuralNetworkPattern: Generate the specified neural network.
generate() - Method in class org.encog.neural.pattern.RadialBasisPattern: Generate the RBF network.
generate() - Method in class org.encog.neural.pattern.RSOMPattern: Generate the RSOM network.
generate() - Method in class org.encog.neural.pattern.SOMPattern: Generate the RSOM network.
generate(int, int, int, double, double) - Static method in class org.encog.util.benchmark.RandomTrainingFactory: Generate a random training set.
GenerateClasslist - Class in org.encog.util: Utility to automatically generate the Encog class list file.
GenerateClasslist() - Constructor for class org.encog.util.GenerateClasslist
generateInputForPrediction(Date) - Method in class org.encog.neural.data.market.MarketNeuralDataSet: To be implemented later.
generateInputNeuralData(int) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Generate input neural data for the specified index.
generateOutputNeuralData(int) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Generate neural ideal data for the specified index.
GenericPersistor - Class in org.encog.persist.persistors.generic: An Encog perisistor that can be used with any object that supports the Encog generic persistence.
GenericPersistor(Class<?>) - Constructor for class org.encog.persist.persistors.generic.GenericPersistor: Construct a generic persistor for the specified class.
GeneticAlgorithm<GENE_TYPE> - Class in org.encog.solve.genetic: Implements a genetic algorithm.
GeneticAlgorithm() - Constructor for class org.encog.solve.genetic.GeneticAlgorithm
get(int, int) - Method in class org.encog.matrix.Matrix: Read the specified cell in the matrix.
get(String) - Method in class org.encog.neural.data.PropertyData: Get the specified property.
get(String) - Method in class org.encog.neural.networks.training.propagation.TrainingContinuation: Get an object by name.
get(int) - Method in class org.encog.util.csv.ReadCSV: Get the specified column as a string.
get(String) - Method in class org.encog.util.csv.ReadCSV: Get the column by its string name, as a string.
getA1() - Method in class org.encog.neural.networks.logic.ART1Logic
getA1() - Method in class org.encog.neural.pattern.ART1Pattern
getAction() - Method in class org.encog.bot.browse.range.Form
getActivationFunction() - Method in class org.encog.neural.data.temporal.TemporalDataDescription
getActivationFunction() - Method in class org.encog.neural.networks.layers.BasicLayer
getActivationFunction() - Method in interface org.encog.neural.networks.layers.Layer
getAllFields(Class<?>) - Static method in class org.encog.util.ReflectionUtil: Get all of the fields from the specified class as a collection.
getAllFields(Class<?>, Collection<Field>) - Static method in class org.encog.util.ReflectionUtil: Get all of the fields in the specified class and super classes.
getAnnealCycles() - Method in class org.encog.neural.pattern.BoltzmannPattern
getArray() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing: Get the network as an array of doubles.
getArray() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealingHelper: Used to pass the getArray call on to the parent object.
getArray() - Method in class org.encog.solve.anneal.SimulatedAnnealing: Subclasses must provide access to an array that makes up the solution.
getArrayCopy() - Method in class org.encog.matrix.Matrix
getArrayCopy() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing
getArrayCopy() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealingHelper: Used to pass the getArrayCopy call on to the parent object.
getArrayCopy() - Method in class org.encog.solve.anneal.SimulatedAnnealing: Get a copy of the array.
getAttributeInt(String) - Method in class org.encog.parse.tags.Tag: Get the specified attribute as an integer.
getAttributes() - Method in class org.encog.bot.rss.RSS: Get the list of attributes.
getAttributes() - Method in class org.encog.parse.tags.Tag: Get a map of all attributes.
getAttributeValue(String) - Method in class org.encog.parse.tags.Tag: Get the value of the specified attribute.
getB1() - Method in class org.encog.neural.networks.logic.ART1Logic
getB1() - Method in class org.encog.neural.pattern.ART1Pattern
getBegin() - Method in class org.encog.bot.browse.range.DocumentRange
getBestNetwork() - Method in class org.encog.neural.prune.PruneIncremental
getBoolean(int) - Method in class org.encog.neural.data.bipolar.BiPolarNeuralData: Get the specified data item as a boolean.
getBoundary() - Static method in class org.encog.util.http.FormUtility: Generate a boundary for a multipart form.
getC1() - Method in class org.encog.neural.networks.logic.ART1Logic
getC1() - Method in class org.encog.neural.pattern.ART1Pattern
getCalculateScore() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing
getCalculateScore() - Method in class org.encog.neural.networks.training.genetic.NeuralGeneticAlgorithm
getCatchAll() - Method in class org.encog.normalize.output.mapped.OutputFieldEncode
getCenter() - Method in class org.encog.util.math.rbf.GaussianFunction
getCenter(int) - Method in class org.encog.util.math.rbf.GaussianFunctionMulti: Get the center for the specified dimension.
getCenter() - Method in interface org.encog.util.math.rbf.RadialBasisFunction
getCenter(int) - Method in interface org.encog.util.math.rbf.RadialBasisFunctionMulti: Get the center of this RBD.
getChromosome(int) - Method in class org.encog.solve.genetic.GeneticAlgorithm: Get a specific chromosome.
getChromosomes() - Method in class org.encog.solve.genetic.GeneticAlgorithm: Return the entire population.
getClassAttribute() - Method in class org.encog.bot.browse.range.DocumentRange
getCode() - Method in class org.encog.bot.dataunit.CodeDataUnit
getCol(int) - Method in class org.encog.matrix.Matrix: Read one entire column from the matrix as a sub-matrix.
getCols() - Method in class org.encog.matrix.Matrix: Get the columns in the matrix.
getColumnCount() - Method in class org.encog.util.csv.ReadCSV: Get the column count.
getConnection() - Method in class org.encog.neural.data.sql.SQLNeuralDataSet
getConsoleHandler() - Static method in class org.encog.util.logging.Logging
getContents() - Method in class org.encog.bot.browse.WebPage
getContents() - Method in class org.encog.neural.networks.training.propagation.TrainingContinuation
getContents() - Method in class org.encog.persist.EncogMemoryCollection
getContext() - Method in class org.encog.neural.networks.layers.ContextLayer
getCount() - Method in class org.encog.neural.networks.training.propagation.gradient.CalculateGradient
getCount() - Method in class org.encog.neural.networks.training.propagation.gradient.GradientUtil
getCount() - Method in class org.encog.neural.networks.training.propagation.gradient.GradientWorker
getCount() - Method in class org.encog.normalize.segregate.IntegerBalanceSegregator
getCSVFormat() - Method in class org.encog.normalize.DataNormalization
getCurrentBlue() - Method in class org.encog.util.downsample.RGBDownsample
getCurrentGreen() - Method in class org.encog.util.downsample.RGBDownsample
getCurrentIndex() - Method in class org.encog.normalize.segregate.index.IndexSegregator
getCurrentPage() - Method in class org.encog.bot.browse.Browser
getCurrentRed() - Method in class org.encog.util.downsample.RGBDownsample
getCurrentState() - Method in class org.encog.neural.networks.logic.ThermalLogic
getCurrentValue() - Method in class org.encog.normalize.input.BasicInputField
getCurrentValue() - Method in interface org.encog.normalize.input.InputField
getCutLength() - Method in class org.encog.solve.genetic.GeneticAlgorithm: Get the cut length.
getCycles() - Method in class org.encog.solve.anneal.SimulatedAnnealing
getD() - Method in class org.encog.matrix.decomposition.EigenvalueDecomposition: Return the block diagonal eigenvalue matrix
getD1() - Method in class org.encog.neural.networks.logic.ART1Logic
getD1() - Method in class org.encog.neural.pattern.ART1Pattern
getData() - Method in class org.encog.bot.browse.WebPage
getData() - Method in class org.encog.matrix.Matrix
getData() - Method in class org.encog.neural.data.basic.BasicNeuralData: Get the data as an array.
getData(int) - Method in class org.encog.neural.data.basic.BasicNeuralData: Get a data value at the specified index.
getData() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Get the data held by this container.
getData() - Method in class org.encog.neural.data.bipolar.BiPolarNeuralData: Get the data held by this object as an array of doubles.
getData(int) - Method in class org.encog.neural.data.bipolar.BiPolarNeuralData: Get the data held by the index.
getData(MarketDataType) - Method in class org.encog.neural.data.market.loader.LoadedMarketData: Get one type of market data from this date.
getData() - Method in interface org.encog.neural.data.NeuralData
getData(int) - Method in interface org.encog.neural.data.NeuralData: Get the element specified index value.
getData() - Method in class org.encog.neural.data.PropertyData: Get all of the property data as a map.
getData() - Method in class org.encog.neural.data.temporal.TemporalPoint
getData(int) - Method in class org.encog.neural.data.temporal.TemporalPoint: Get the data at the specified index.
getDataset() - Method in class org.encog.normalize.target.NormalizationStorageNeuralDataSet
getDataSize() - Method in class org.encog.bot.browse.WebPage: Get the number of data items in this collection.
getDataType() - Method in class org.encog.neural.data.market.MarketDataDescription
getDataUnit(int) - Method in class org.encog.bot.browse.WebPage: Get the DataUnit unit at the specified index.
getDate() - Method in class org.encog.bot.rss.RSSItem: Get the publication date.
getDate(String) - Method in class org.encog.neural.data.PropertyData: Get a property as a date.
getDate(String) - Method in class org.encog.util.csv.ReadCSV: Get the column as a date.
getDecimal() - Method in class org.encog.util.csv.CSVFormat
getDecimalCharacter() - Static method in class org.encog.util.csv.CSVFormat: Get the decimal character currently in use by the computer's default location.
getDepth(Layer) - Method in class org.encog.neural.networks.structure.CalculateDepth: Get the depth for a specific layer.
getDescription() - Method in class org.encog.bot.rss.RSSItem: Get the description.
getDescription() - Method in class org.encog.matrix.Matrix
getDescription() - Method in class org.encog.neural.activation.BasicActivationFunction
getDescription() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet
getDescription() - Method in class org.encog.neural.data.PropertyData
getDescription() - Method in class org.encog.neural.data.TextData
getDescription() - Method in class org.encog.neural.networks.BasicNetwork
getDescription() - Method in class org.encog.neural.networks.layers.BasicLayer
getDescription() - Method in interface org.encog.neural.networks.Network
getDescription() - Method in class org.encog.neural.networks.synapse.BasicSynapse: The EncogPersistedObject requires a name and description, however, these are not used on synapses.
getDescription() - Method in class org.encog.neural.networks.training.propagation.TrainingContinuation
getDescription() - Method in class org.encog.normalize.DataNormalization
getDescription() - Method in class org.encog.persist.DirectoryEntry
getDescription() - Method in interface org.encog.persist.EncogPersistedObject
getDescriptions() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
getDesiredSetSize() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
getDimensions() - Method in class org.encog.util.math.rbf.GaussianFunctionMulti
getDimensions() - Method in interface org.encog.util.math.rbf.RadialBasisFunctionMulti
getDirectory() - Method in class org.encog.persist.EncogPersistedCollection
getDistance(double[], int) - Method in class org.encog.util.math.Equilateral: Get the Euclidean distance between the specified data and the set number.
getDouble(String) - Method in class org.encog.neural.data.PropertyData: Get a property as a double.
getDouble(int) - Method in class org.encog.util.csv.ReadCSV: Get the column as a double specified by index.
getDouble(String) - Method in class org.encog.util.csv.ReadCSV: Get the specified column as a double.
getDoublePivot() - Method in class org.encog.matrix.decomposition.LUDecomposition: Return pivot permutation vector as a one-dimensional double array
getDownSampleBottom() - Method in interface org.encog.util.downsample.Downsample
getDownSampleBottom() - Method in class org.encog.util.downsample.RGBDownsample
getDownSampleLeft() - Method in interface org.encog.util.downsample.Downsample
getDownSampleLeft() - Method in class org.encog.util.downsample.RGBDownsample
getDownSampleRight() - Method in interface org.encog.util.downsample.Downsample
getDownSampleRight() - Method in class org.encog.util.downsample.RGBDownsample
getDownSampleTop() - Method in interface org.encog.util.downsample.Downsample
getDownSampleTop() - Method in class org.encog.util.downsample.RGBDownsample
getElements() - Method in class org.encog.bot.browse.range.DocumentRange
getEncogVersion() - Method in class org.encog.persist.EncogMemoryCollection
getEncogVersion() - Method in class org.encog.persist.EncogPersistedCollection
getEnd() - Method in class org.encog.bot.browse.range.DocumentRange
getEndingIndex() - Method in class org.encog.normalize.segregate.index.IndexRangeSegregator
getEndingIndex() - Method in class org.encog.normalize.segregate.index.IndexSampleSegregator
getEquilateral() - Method in class org.encog.normalize.output.nominal.OutputEquilateral
getError() - Method in class org.encog.neural.networks.training.BasicTraining: Get the current error percent from the training.
getError() - Method in class org.encog.neural.networks.training.genetic.NeuralGeneticAlgorithm.NeuralGeneticAlgorithmHelper
getError() - Method in class org.encog.neural.networks.training.propagation.gradient.CalculateGradient
getError() - Method in class org.encog.neural.networks.training.propagation.gradient.GradientUtil
getError() - Method in class org.encog.neural.networks.training.propagation.gradient.GradientWorker
getError() - Method in interface org.encog.neural.networks.training.Train: Get the current error percent from the training.
getErrors() - Method in class org.encog.neural.networks.training.propagation.gradient.GradientUtil
getErrors() - Method in class org.encog.neural.networks.training.propagation.gradient.GradientWorker
getExchange() - Method in class org.encog.neural.data.market.TickerSymbol
getF1Neurons() - Method in class org.encog.neural.networks.logic.BAMLogic
getF2Neurons() - Method in class org.encog.neural.networks.logic.BAMLogic
getFalseValue() - Method in class org.encog.normalize.output.nominal.OutputOneOf
getField() - Method in class org.encog.normalize.input.NeuralDataFieldHolder
getField() - Method in class org.encog.normalize.output.OutputFieldRangeMapped
getField() - Method in class org.encog.persist.persistors.generic.FieldMapping
getFile() - Method in class org.encog.normalize.input.InputFieldCSV
getFile() - Method in class org.encog.persist.location.FilePersistence
getFilename() - Method in class org.encog.neural.data.csv.CSVNeuralDataSet
getFilename() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet
getFileVersion() - Method in class org.encog.persist.EncogMemoryCollection
getFileVersion() - Method in class org.encog.persist.EncogPersistedCollection
getFormat() - Method in class org.encog.neural.data.csv.CSVNeuralDataSet
getFrom() - Method in class org.encog.neural.networks.NeuralDataMapping
getFrom() - Method in class org.encog.util.time.TimeSpan
getFromLayer() - Method in class org.encog.neural.networks.synapse.BasicSynapse
getFromLayer() - Method in interface org.encog.neural.networks.synapse.Synapse
getFromNeuronCount() - Method in class org.encog.neural.networks.synapse.BasicSynapse
getFromNeuronCount() - Method in interface org.encog.neural.networks.synapse.Synapse
getGausian() - Method in class org.encog.neural.activation.ActivationGaussian
getGene(int) - Method in class org.encog.solve.genetic.Chromosome: Get the specified gene.
getGenes() - Method in class org.encog.solve.genetic.Chromosome: Used the get the entire gene array.
getGenetic() - Method in class org.encog.neural.networks.training.genetic.NeuralGeneticAlgorithm
getGeneticAlgorithm() - Method in class org.encog.solve.genetic.Chromosome
getGradients() - Method in class org.encog.neural.networks.training.propagation.gradient.CalculateGradient
getGroup() - Method in class org.encog.normalize.output.OutputFieldGrouped
getGroupedFields() - Method in class org.encog.normalize.output.BasicOutputFieldGroup
getGroupedFields() - Method in interface org.encog.normalize.output.OutputFieldGroup
getGroups() - Method in class org.encog.normalize.DataNormalization
getH() - Method in class org.encog.matrix.decomposition.QRDecomposition: Return the Householder vectors
getHeight() - Method in class org.encog.neural.data.image.ImageNeuralDataSet
getHeight() - Method in class org.encog.util.ImageSize
getHidden() - Method in class org.encog.neural.prune.PruneIncremental
getHigh() - Method in class org.encog.neural.data.temporal.TemporalDataDescription
getHigh() - Method in class org.encog.normalize.output.mapped.MappedRange
getHigh() - Method in class org.encog.normalize.output.nominal.NominalItem
getHigh() - Method in class org.encog.normalize.output.nominal.OutputEquilateral
getHigh() - Method in class org.encog.normalize.output.OutputFieldRangeMapped
getHigh() - Method in class org.encog.normalize.segregate.SegregationRange
getHighSequence() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
getID() - Method in class org.encog.neural.networks.layers.BasicLayer
getID() - Method in interface org.encog.neural.networks.layers.Layer
getIdAttribute() - Method in class org.encog.bot.browse.range.DocumentRange
getIdeal() - Method in class org.encog.neural.data.basic.BasicNeuralDataPair: Get the expected results.
getIdeal() - Method in interface org.encog.neural.data.NeuralDataPair
getIdealSize() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Get the size of the ideal dataset.
getIdealSize() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet
getIdealSize() - Method in class org.encog.neural.data.csv.CSVNeuralDataSet
getIdealSize() - Method in interface org.encog.neural.data.NeuralDataSet
getIdealSize() - Method in class org.encog.neural.data.sql.SQLNeuralDataSet
getIdealSize() - Method in class org.encog.neural.data.union.UnionNeuralDataSet
getIdealSize() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet
getIdealXML() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet
getImage() - Method in class org.encog.neural.data.image.ImageNeuralData
getImageHeight() - Method in interface org.encog.util.downsample.Downsample
getImageHeight() - Method in class org.encog.util.downsample.RGBDownsample
getImagEigenvalues() - Method in class org.encog.matrix.decomposition.EigenvalueDecomposition: Return the imaginary parts of the eigenvalues.
getImageWidth() - Method in interface org.encog.util.downsample.Downsample
getImageWidth() - Method in class org.encog.util.downsample.RGBDownsample
getIncrement() - Method in class org.encog.util.math.LinearCongruentialGenerator
getIndex() - Method in class org.encog.neural.data.temporal.TemporalDataDescription
getInitialUpdate() - Method in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation
getInput() - Method in class org.encog.neural.data.basic.BasicNeuralDataPair: Get the input data.
getInput() - Method in interface org.encog.neural.data.NeuralDataPair
getInputField() - Method in class org.encog.normalize.output.nominal.NominalItem
getInputFields() - Method in class org.encog.normalize.DataNormalization
getInputLayer() - Method in class org.encog.neural.networks.training.cpn.FindCPN
getInputNeuronCount() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
getInputNeuronCount() - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining
getInputSize() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Get the size of the input dataset.
getInputSize() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet
getInputSize() - Method in class org.encog.neural.data.csv.CSVNeuralDataSet
getInputSize() - Method in interface org.encog.neural.data.NeuralDataSet
getInputSize() - Method in class org.encog.neural.data.sql.SQLNeuralDataSet
getInputSize() - Method in class org.encog.neural.data.union.UnionNeuralDataSet
getInputSize() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet
getInputWindowSize() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
getInputXML() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet
getInstance() - Static method in class org.encog.Encog: Get the instance to the singleton.
getInstance() - Static method in class org.encog.util.concurrency.EncogConcurrency
getInstarLayer() - Method in class org.encog.neural.networks.training.cpn.FindCPN
getInstarSynapse() - Method in class org.encog.neural.networks.training.cpn.FindCPN
getInt(String) - Method in class org.encog.util.csv.ReadCSV: Obtain a column as an integer referenced by a string.
getInteger(String) - Method in class org.encog.neural.data.PropertyData: Get a property as an integer.
getItems() - Method in class org.encog.bot.rss.RSS
getIterations() - Method in class org.encog.neural.prune.PruneIncremental
getIterator() - Method in class org.encog.normalize.input.NeuralDataFieldHolder
getJobUnit() - Method in class org.encog.util.concurrency.job.JobUnitContext
getL() - Method in class org.encog.matrix.decomposition.CholeskyDecomposition: Return triangular factor.
getL() - Method in class org.encog.matrix.decomposition.LUDecomposition: Return lower triangular factor
getL() - Method in class org.encog.neural.networks.logic.ART1Logic
getL() - Method in class org.encog.neural.pattern.ART1Pattern
getLayer(String) - Method in class org.encog.neural.networks.BasicNetwork: Get the layer specified by the tag.
getLayers() - Method in class org.encog.neural.networks.structure.NeuralStructure
getLayerTags() - Method in class org.encog.neural.networks.BasicNetwork
getLearningRate() - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining
getLearningRate() - Method in class org.encog.neural.networks.training.cpn.TrainInstar
getLearningRate() - Method in class org.encog.neural.networks.training.cpn.TrainOutstar
getLearningRate() - Method in interface org.encog.neural.networks.training.LearningRate
getLearningRate() - Method in class org.encog.neural.networks.training.propagation.back.Backpropagation
getLearningRate() - Method in class org.encog.neural.networks.training.propagation.manhattan.ManhattanPropagation
getLearningRate() - Method in class org.encog.neural.networks.training.simple.TrainAdaline
getLength() - Method in class org.encog.normalize.output.multiplicative.MultiplicativeGroup
getLength() - Method in class org.encog.normalize.output.zaxis.ZAxisGroup
getLink() - Method in class org.encog.bot.rss.RSSItem: Get the hyperlink.
getLoader() - Method in class org.encog.neural.data.market.MarketNeuralDataSet
getLogic() - Method in class org.encog.neural.networks.BasicNetwork
getLow() - Method in class org.encog.neural.data.temporal.TemporalDataDescription
getLow() - Method in class org.encog.normalize.output.mapped.MappedRange
getLow() - Method in class org.encog.normalize.output.nominal.NominalItem
getLow() - Method in class org.encog.normalize.output.nominal.OutputEquilateral
getLow() - Method in class org.encog.normalize.output.OutputFieldRangeMapped
getLow() - Method in class org.encog.normalize.segregate.SegregationRange
getLowSequence() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
getMap() - Method in class org.encog.util.http.CookieUtility: Allows access to the name/value pair list of cookies.
getMatingPopulation() - Method in class org.encog.solve.genetic.GeneticAlgorithm: Get the mating population.
getMatrix(int, int, int, int) - Method in class org.encog.matrix.Matrix: Get a submatrix.
getMatrix(int[], int[]) - Method in class org.encog.matrix.Matrix: Get a submatrix.
getMatrix(int, int, int[]) - Method in class org.encog.matrix.Matrix: Get a submatrix.
getMatrix(int[], int, int) - Method in class org.encog.matrix.Matrix: Get a submatrix.
getMatrix() - Method in class org.encog.neural.networks.synapse.DirectSynapse
getMatrix() - Method in class org.encog.neural.networks.synapse.OneToOneSynapse
getMatrix() - Method in interface org.encog.neural.networks.synapse.Synapse: Get the weight and threshold matrix.
getMatrix() - Method in class org.encog.neural.networks.synapse.WeightedSynapse: Get the weight and threshold matrix.
getMatrix() - Method in class org.encog.neural.networks.synapse.WeightlessSynapse
getMatrixSize() - Method in class org.encog.neural.networks.synapse.DirectSynapse
getMatrixSize() - Method in class org.encog.neural.networks.synapse.OneToOneSynapse
getMatrixSize() - Method in interface org.encog.neural.networks.synapse.Synapse: Get the size of the matrix, or zero if one is not defined.
getMatrixSize() - Method in class org.encog.neural.networks.synapse.WeightedSynapse: Get the size of the matrix, or zero if one is not defined.
getMatrixSize() - Method in class org.encog.neural.networks.synapse.WeightlessSynapse
getMax() - Method in class org.encog.neural.prune.HiddenLayerParams
getMax() - Method in class org.encog.normalize.input.BasicInputField
getMax() - Method in interface org.encog.normalize.input.InputField
getMaxStep() - Method in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation
getMaxWinners() - Method in class org.encog.neural.activation.ActivationCompetitive
getMethod() - Method in class org.encog.bot.browse.range.Form
getMin() - Method in class org.encog.neural.prune.HiddenLayerParams
getMin() - Method in class org.encog.normalize.input.BasicInputField
getMin() - Method in interface org.encog.normalize.input.InputField
getModulus() - Method in class org.encog.util.math.LinearCongruentialGenerator
getMomentum() - Method in interface org.encog.neural.networks.training.Momentum
getMomentum() - Method in class org.encog.neural.networks.training.propagation.back.Backpropagation
getMultiplier() - Method in class org.encog.normalize.output.zaxis.ZAxisGroup
getMultiplier() - Method in class org.encog.util.math.LinearCongruentialGenerator
getMutationPercent() - Method in class org.encog.solve.genetic.GeneticAlgorithm: Get the mutation percent.
getName() - Method in class org.encog.bot.browse.range.FormElement
getName() - Method in class org.encog.matrix.Matrix
getName() - Method in class org.encog.neural.activation.BasicActivationFunction
getName() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet
getName() - Method in class org.encog.neural.data.PropertyData
getName() - Method in class org.encog.neural.data.TextData
getName() - Method in class org.encog.neural.networks.BasicNetwork
getName() - Method in class org.encog.neural.networks.layers.BasicLayer
getName() - Method in interface org.encog.neural.networks.Network
getName() - Method in class org.encog.neural.networks.synapse.BasicSynapse: The EncogPersistedObject requires a name and description, however, these are not used on synapses.
getName() - Method in class org.encog.neural.networks.training.propagation.TrainingContinuation
getName() - Method in class org.encog.normalize.DataNormalization
getName() - Method in class org.encog.parse.tags.Tag
getName() - Method in class org.encog.persist.DirectoryEntry
getName() - Method in interface org.encog.persist.EncogPersistedObject
getNeighborhood() - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining
getNetwork() - Method in class org.encog.neural.networks.layers.BasicLayer
getNetwork() - Method in interface org.encog.neural.networks.layers.Layer
getNetwork() - Method in class org.encog.neural.networks.logic.ARTLogic
getNetwork() - Method in class org.encog.neural.networks.logic.BAMLogic
getNetwork() - Method in class org.encog.neural.networks.logic.FeedforwardLogic
getNetwork() - Method in class org.encog.neural.networks.structure.NeuralStructure
getNetwork() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing: Get the best network from the training.
getNetwork() - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining
getNetwork() - Method in class org.encog.neural.networks.training.cpn.TrainInstar
getNetwork() - Method in class org.encog.neural.networks.training.cpn.TrainOutstar
getNetwork() - Method in class org.encog.neural.networks.training.genetic.NeuralChromosome
getNetwork() - Method in class org.encog.neural.networks.training.genetic.NeuralGeneticAlgorithm
getNetwork() - Method in class org.encog.neural.networks.training.genetic.NeuralGeneticAlgorithm.NeuralGeneticAlgorithmHelper: Get the current best neural network.
getNetwork() - Method in class org.encog.neural.networks.training.propagation.gradient.CalculateGradient
getNetwork() - Method in class org.encog.neural.networks.training.propagation.gradient.GradientWorker
getNetwork() - Method in class org.encog.neural.networks.training.propagation.Propagation
getNetwork() - Method in class org.encog.neural.networks.training.simple.TrainAdaline
getNetwork() - Method in interface org.encog.neural.networks.training.Train: Get the current best network from the training.
getNetwork() - Method in class org.encog.neural.prune.PruneSelective
getNetworkInputLayerSize() - Method in class org.encog.normalize.DataNormalization
getNetworkOutputLayerSize() - Method in class org.encog.normalize.DataNormalization
getNeuralDataSet() - Method in class org.encog.normalize.input.InputFieldNeuralDataSet
getNeuronCount() - Method in class org.encog.neural.networks.layers.BasicLayer: Get the neuron count for this layer.
getNeuronCount() - Method in interface org.encog.neural.networks.layers.Layer
getNeuronCount() - Method in class org.encog.neural.networks.logic.ThermalLogic
getNext() - Method in class org.encog.neural.networks.layers.BasicLayer
getNext() - Method in interface org.encog.neural.networks.layers.Layer: Get a list of all of the outbound synapse connections from this layer.
getNextID() - Method in class org.encog.neural.networks.structure.NeuralStructure: Get the next layer id.
getNextLayers() - Method in class org.encog.neural.networks.layers.BasicLayer
getNextLayers() - Method in interface org.encog.neural.networks.layers.Layer
getNormalization() - Method in class org.encog.normalize.segregate.index.IndexSegregator
getNormalization() - Method in class org.encog.normalize.segregate.IntegerBalanceSegregator
getNormalization() - Method in class org.encog.normalize.segregate.RangeSegregator
getNormalization() - Method in interface org.encog.normalize.segregate.Segregator
getNumberFormatter() - Method in class org.encog.util.csv.CSVFormat
getNumThreads() - Method in class org.encog.neural.networks.training.propagation.Propagation
getOffset() - Method in class org.encog.normalize.input.InputFieldCSV
getOffset() - Method in class org.encog.normalize.input.InputFieldNeuralDataSet
getOriginal() - Method in class org.encog.bot.browse.Address
getOutput() - Method in class org.encog.neural.networks.NeuralOutputHolder
getOutputFieldCount() - Method in class org.encog.normalize.DataNormalization
getOutputFields() - Method in class org.encog.normalize.DataNormalization
getOutputNeuronCount() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
getOutputNeuronCount() - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining
getOutstarLayer() - Method in class org.encog.neural.networks.training.cpn.FindCPN
getOutstarSynapse() - Method in class org.encog.neural.networks.training.cpn.FindCPN
getOwner() - Method in class org.encog.bot.browse.range.FormElement
getOwner() - Method in class org.encog.util.concurrency.job.JobUnitContext
getPair() - Method in class org.encog.normalize.input.NeuralDataFieldHolder
getPairXML() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet
getParent() - Method in class org.encog.bot.browse.range.DocumentRange
getPattern() - Method in class org.encog.neural.prune.PruneIncremental
getPeak() - Method in class org.encog.util.math.rbf.GaussianFunction
getPeak() - Method in class org.encog.util.math.rbf.GaussianFunctionMulti
getPeak() - Method in interface org.encog.util.math.rbf.RadialBasisFunction
getPeak() - Method in interface org.encog.util.math.rbf.RadialBasisFunctionMulti: Get the center of this RBD.
getPercentToMate() - Method in class org.encog.solve.genetic.GeneticAlgorithm: Get the percent to mate.
getPivot() - Method in class org.encog.matrix.decomposition.LUDecomposition: Return pivot permutation vector
getPixelMap() - Method in interface org.encog.util.downsample.Downsample
getPixelMap() - Method in class org.encog.util.downsample.RGBDownsample
getPlatform() - Method in class org.encog.persist.EncogMemoryCollection
getPlatform() - Method in class org.encog.persist.EncogPersistedCollection
getPoints() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
getPopulationSize() - Method in class org.encog.solve.genetic.GeneticAlgorithm: Get the population size.
getPredictWindowSize() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
getPreviousLayers(Layer) - Method in class org.encog.neural.networks.structure.NeuralStructure: Get the previous layers from the specified layer.
getPreviousSynapses(Layer) - Method in class org.encog.neural.networks.structure.NeuralStructure: Get the previous synapses.
getProperties() - Method in class org.encog.Encog
getProperties() - Method in class org.encog.neural.networks.BasicNetwork
getPropertyDouble(String) - Method in class org.encog.neural.networks.BasicNetwork: Get the specified property as a double.
getPropertyLong(String) - Method in class org.encog.neural.networks.BasicNetwork: Get the specified property as a long.
getPropertyString(String) - Method in class org.encog.neural.networks.BasicNetwork: Get the specified property as a string.
getQ() - Method in class org.encog.matrix.decomposition.QRDecomposition: Generate and return the (economy-sized) orthogonal factor
getR() - Method in class org.encog.matrix.decomposition.QRDecomposition: Return the upper triangular factor
getRadialBasisFunction() - Method in class org.encog.neural.networks.layers.RadialBasisFunctionLayer
getRadius() - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodBubble
getRadius() - Method in interface org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodFunction
getRadius() - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodGaussian
getRadius() - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodGaussianMulti
getRadius() - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodSingle: The radius for this neighborhood function is always 1.
getRatioX() - Method in interface org.encog.util.downsample.Downsample
getRatioX() - Method in class org.encog.util.downsample.RGBDownsample
getRatioY() - Method in interface org.encog.util.downsample.Downsample
getRatioY() - Method in class org.encog.util.downsample.RGBDownsample
getRBF() - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodGaussianMulti
getRealEigenvalues() - Method in class org.encog.matrix.decomposition.EigenvalueDecomposition: Return the real parts of the eigenvalues.
getRecord(long, NeuralDataPair) - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Get a record by index into the specified pair.
getRecord(long, NeuralDataPair) - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet: Get a record by index and copy it into the specified pair.
getRecord(long, NeuralDataPair) - Method in interface org.encog.neural.data.Indexable: Read an individual record, specified by index, in random order.
getRecordCount() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet
getRecordCount() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet
getRecordCount() - Method in interface org.encog.neural.data.Indexable: Determine the total number of records in the set.
getRecordCount() - Method in class org.encog.normalize.DataNormalization
getRef() - Method in class org.encog.persist.persistors.generic.FieldMapping
getReference(Object) - Method in class org.encog.persist.persistors.generic.ObjectTagger: Get the reference for the specified object.
getReport() - Method in class org.encog.normalize.DataNormalization
getResult() - Method in class org.encog.neural.networks.NeuralOutputHolder
getRootLogger() - Static method in class org.encog.util.logging.Logging
getRow(int) - Method in class org.encog.matrix.Matrix: Get the specified row as a sub-matrix.
getRows() - Method in class org.encog.matrix.Matrix: Get the number of rows in the matrix.
getRunCycles() - Method in class org.encog.neural.pattern.BoltzmannPattern
getRunningCounts() - Method in class org.encog.normalize.segregate.IntegerBalanceSegregator
getS() - Method in class org.encog.matrix.decomposition.SingularValueDecomposition: Return the diagonal matrix of singular values
getSampleSize() - Method in class org.encog.normalize.segregate.index.IndexSampleSegregator
getScore() - Method in class org.encog.solve.anneal.SimulatedAnnealing
getScore() - Method in class org.encog.solve.genetic.Chromosome
getSeed() - Method in class org.encog.util.math.LinearCongruentialGenerator
getSegregators() - Method in class org.encog.normalize.DataNormalization
getSeparator() - Method in class org.encog.util.csv.CSVFormat
getSequence() - Method in class org.encog.neural.data.temporal.TemporalPoint
getSequenceFromDate(Date) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Create a sequence number from a time.
getSequenceGrandularity() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
getShouldMinimize() - Method in class org.encog.solve.genetic.GeneticAlgorithm
getSingularValues() - Method in class org.encog.matrix.decomposition.SingularValueDecomposition: Return the one-dimensional array of singular values
getSource() - Method in class org.encog.bot.browse.range.DocumentRange
getSourceField() - Method in class org.encog.normalize.output.mapped.OutputFieldEncode
getSourceField() - Method in class org.encog.normalize.output.OutputFieldGrouped
getSourceField() - Method in class org.encog.normalize.segregate.RangeSegregator
getSpan(TimeUnit) - Method in class org.encog.util.time.TimeSpan: Get the time span specified by the unit.
getStartingIndex() - Method in class org.encog.normalize.segregate.index.IndexRangeSegregator
getStartingIndex() - Method in class org.encog.normalize.segregate.index.IndexSampleSegregator
getStartingPoint() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
getStartTemperature() - Method in class org.encog.solve.anneal.SimulatedAnnealing
getStatement() - Method in class org.encog.neural.data.sql.SQLNeuralDataSet
getStopTemperature() - Method in class org.encog.solve.anneal.SimulatedAnnealing
getStorage() - Method in class org.encog.normalize.DataNormalization
getStrategies() - Method in class org.encog.neural.networks.training.BasicTraining
getStrategies() - Method in interface org.encog.neural.networks.training.Train
getStructure() - Method in class org.encog.neural.networks.BasicNetwork
getStructure() - Method in interface org.encog.neural.networks.Network
getSubfieldCount() - Method in class org.encog.normalize.output.mapped.OutputFieldEncode
getSubfieldCount() - Method in class org.encog.normalize.output.multiplicative.OutputFieldMultiplicative
getSubfieldCount() - Method in class org.encog.normalize.output.nominal.OutputEquilateral: This is the total number of nominal items minus 1.
getSubfieldCount() - Method in class org.encog.normalize.output.nominal.OutputOneOf
getSubfieldCount() - Method in interface org.encog.normalize.output.OutputField
getSubfieldCount() - Method in class org.encog.normalize.output.OutputFieldDirect
getSubfieldCount() - Method in class org.encog.normalize.output.OutputFieldRangeMapped
getSubfieldCount() - Method in class org.encog.normalize.output.zaxis.OutputFieldZAxis
getSubfieldCount() - Method in class org.encog.normalize.output.zaxis.OutputFieldZAxisSynthetic
getSubsets() - Method in class org.encog.neural.data.union.UnionNeuralDataSet
getSymbol() - Method in class org.encog.neural.data.market.TickerSymbol
getSynapses() - Method in class org.encog.neural.networks.structure.NeuralStructure
getTag() - Method in class org.encog.bot.dataunit.TagDataUnit
getTag() - Method in class org.encog.parse.tags.read.ReadTags: Return the last tag found, this is normally called just after the read function returns a zero.
getTags(Layer) - Method in class org.encog.neural.networks.BasicNetwork: Get a list of all of the tags on a specific layer.
getTarget() - Method in class org.encog.bot.browse.range.Link
getTarget() - Method in class org.encog.normalize.segregate.IntegerBalanceSegregator
getTarget() - Method in class org.encog.persist.persistors.generic.FieldMapping
getTaskNumber() - Method in class org.encog.util.concurrency.job.JobUnitContext
getTemperature() - Method in class org.encog.neural.networks.logic.BoltzmannLogic
getTemperature() - Method in class org.encog.neural.pattern.BoltzmannPattern
getTemperature() - Method in class org.encog.solve.anneal.SimulatedAnnealing
getText() - Method in class org.encog.bot.dataunit.TextDataUnit
getText() - Method in class org.encog.neural.data.TextData
getTextOnly() - Method in class org.encog.bot.browse.range.DocumentRange: Get the text from this range.
getThermalLayer() - Method in class org.encog.neural.networks.logic.ThermalLogic
getThermalSynapse() - Method in class org.encog.neural.networks.logic.ThermalLogic
getThreshold() - Method in class org.encog.neural.networks.layers.BasicLayer
getThreshold(int) - Method in class org.encog.neural.networks.layers.BasicLayer: Get an individual threshold value.
getThreshold() - Method in interface org.encog.neural.networks.layers.Layer
getThreshold(int) - Method in interface org.encog.neural.networks.layers.Layer: Get an idividual threshold value.
getTicker() - Method in class org.encog.neural.data.market.loader.LoadedMarketData
getTicker() - Method in class org.encog.neural.data.market.MarketDataDescription
getTitle() - Method in class org.encog.bot.browse.WebPage: Get the title for this document.
getTitle() - Method in class org.encog.bot.rss.RSSItem: Get the item title.
getTo() - Method in class org.encog.neural.networks.NeuralDataMapping
getTo() - Method in class org.encog.util.time.TimeSpan
getToLayer() - Method in class org.encog.neural.networks.synapse.BasicSynapse
getToLayer() - Method in interface org.encog.neural.networks.synapse.Synapse
getToNeuronCount() - Method in class org.encog.neural.networks.synapse.BasicSynapse
getToNeuronCount() - Method in interface org.encog.neural.networks.synapse.Synapse
getTraining() - Method in class org.encog.neural.networks.training.BasicTraining
getTraining() - Method in interface org.encog.neural.networks.training.Train
getTraining() - Method in class org.encog.neural.prune.PruneIncremental
getTrueValue() - Method in class org.encog.normalize.output.nominal.OutputOneOf
getType() - Method in class org.encog.bot.browse.range.Input
getType() - Method in class org.encog.neural.data.temporal.TemporalDataDescription
getType() - Method in class org.encog.neural.networks.synapse.DirectSynapse
getType() - Method in class org.encog.neural.networks.synapse.OneToOneSynapse
getType() - Method in interface org.encog.neural.networks.synapse.Synapse
getType() - Method in class org.encog.neural.networks.synapse.WeightedSynapse
getType() - Method in class org.encog.neural.networks.synapse.WeightlessSynapse
getType() - Method in class org.encog.parse.tags.Tag
getType() - Method in class org.encog.persist.DirectoryEntry
getU() - Method in class org.encog.matrix.decomposition.LUDecomposition: Return upper triangular factor
getU() - Method in class org.encog.matrix.decomposition.SingularValueDecomposition: Return the left singular vectors
getUrl() - Method in class org.encog.bot.browse.Address
getUsedForNetworkInput() - Method in class org.encog.normalize.input.BasicInputField
getUsedForNetworkInput() - Method in interface org.encog.normalize.input.InputField
getV() - Method in class org.encog.matrix.decomposition.EigenvalueDecomposition: Return the eigenvector matrix.
getV() - Method in class org.encog.matrix.decomposition.SingularValueDecomposition: Return the right singular vectors
getValue() - Method in class org.encog.bot.browse.range.FormElement
getValue(int) - Method in class org.encog.normalize.input.BasicInputField: Not supported for this sort of class, may be implemented in subclasses.
getValue(int) - Method in interface org.encog.normalize.input.InputField: Called for input field types that require an index to get the current value.
getValue(int) - Method in class org.encog.normalize.input.InputFieldArray1D: Get the value from the specified index.
getValue(int) - Method in class org.encog.normalize.input.InputFieldArray2D: Read a value from the specified index.
getValue() - Method in class org.encog.normalize.output.mapped.MappedRange
getValueXML() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet
getVigilance() - Method in class org.encog.neural.networks.logic.ART1Logic
getVigilance() - Method in class org.encog.neural.pattern.ART1Pattern
getWeightMatrixSize() - Method in class org.encog.neural.networks.BasicNetwork
getWeightMatrixSize() - Method in interface org.encog.neural.networks.Network
getWeights() - Method in class org.encog.neural.networks.training.propagation.gradient.CalculateGradient
getWhen() - Method in class org.encog.neural.data.market.loader.LoadedMarketData
getWhen() - Method in class org.encog.neural.data.market.MarketPoint
getWidth() - Method in class org.encog.neural.data.image.ImageNeuralDataSet
getWidth() - Method in class org.encog.util.ImageSize
getWidth() - Method in class org.encog.util.math.rbf.GaussianFunction
getWidth(int) - Method in class org.encog.util.math.rbf.GaussianFunctionMulti: Get the width for one dimension.
getWidth() - Method in interface org.encog.util.math.rbf.RadialBasisFunction
getWidth(int) - Method in interface org.encog.util.math.rbf.RadialBasisFunctionMulti: Get the center of this RBD.
getWinner() - Method in class org.encog.neural.networks.logic.ART1Logic
getWorstDistance() - Method in class org.encog.neural.networks.training.competitive.BestMatchingUnit
getX() - Method in class org.encog.neural.networks.layers.BasicLayer
getX() - Method in interface org.encog.neural.networks.layers.Layer
getXMLInput() - Method in class org.encog.persist.PersistReader
getXMLText(Node) - Static method in class org.encog.bot.rss.RSS: Simple utility method that obtains the text of an XML node.
getY() - Method in class org.encog.neural.networks.layers.BasicLayer
getY() - Method in interface org.encog.neural.networks.layers.Layer
getZeroTolerance() - Method in class org.encog.neural.networks.training.propagation.manhattan.ManhattanPropagation
getZeroTolerance() - Method in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation
GradientUtil - Class in org.encog.neural.networks.training.propagation.gradient: Single threaded class that actually calculates the gradients.
GradientUtil(BasicNetwork) - Constructor for class org.encog.neural.networks.training.propagation.gradient.GradientUtil: Construct the gradient utility.
GradientWorker - Class in org.encog.neural.networks.training.propagation.gradient: A worker handles one thread.
GradientWorker(CalculateGradient, NeuralDataSet, int, int) - Constructor for class org.encog.neural.networks.training.propagation.gradient.GradientWorker: Construct a worker.
Greedy - Class in org.encog.neural.networks.training.strategy: A simple greedy strategy.
Greedy() - Constructor for class org.encog.neural.networks.training.strategy.Greedy

H

handleItem(ReadXML) - Method in class org.encog.persist.persistors.TrainingContinuationPersistor: Handle an item.
handleItems(ReadXML) - Method in class org.encog.persist.persistors.TrainingContinuationPersistor: Handle loading the items.
hasDerivative() - Method in class org.encog.neural.activation.ActivationBiPolar
hasDerivative() - Method in class org.encog.neural.activation.ActivationCompetitive
hasDerivative() - Method in interface org.encog.neural.activation.ActivationFunction
hasDerivative() - Method in class org.encog.neural.activation.ActivationGaussian
hasDerivative() - Method in class org.encog.neural.activation.ActivationLinear
hasDerivative() - Method in class org.encog.neural.activation.ActivationLOG
hasDerivative() - Method in class org.encog.neural.activation.ActivationSigmoid
hasDerivative() - Method in class org.encog.neural.activation.ActivationSIN
hasDerivative() - Method in class org.encog.neural.activation.ActivationSoftMax
hasDerivative() - Method in class org.encog.neural.activation.ActivationTANH
HasFixedLength - Interface in org.encog.normalize.input: Is this input field of a fixed length, such as an array? Or is it read "iterator style" where we call "next" until there is no more data.
hashCode() - Method in class org.encog.matrix.Matrix: Compute a hash code for this matrix.
hashCode() - Method in class org.encog.neural.data.market.TickerSymbol: Generate a valid hash code.
hashCode() - Method in class org.encog.neural.networks.BasicNetwork: Generate a hash code.
hashCode() - Method in interface org.encog.neural.networks.Network: Generate a hash code.
hashCode() - Method in class org.encog.persist.DirectoryEntry
hasNext() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet.BasicNeuralIterator: Is there more data for the iterator to read?
hasNext() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet.BufferedNeuralDataSetIterator
hasNext() - Method in class org.encog.neural.data.csv.CSVNeuralDataSet.CSVNeuralIterator: Determine if there is more data to be read.
hasNext() - Method in class org.encog.neural.data.sql.SQLNeuralDataSet.SQLNeuralIterator: Returns true if there is more data to be read.
hasNext() - Method in class org.encog.neural.data.union.UnionNeuralDataSet.UnionIterator: Determine if there is more data to be read from this iterator.
hasNext() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet.XMLNeuralIterator: Is there any more data to read?
hasReference(Object) - Method in class org.encog.persist.persistors.generic.ObjectTagger: Returns true if the object has a reference.
hasThreshold() - Method in class org.encog.neural.networks.layers.BasicLayer
hasThreshold() - Method in interface org.encog.neural.networks.layers.Layer
hasWinner() - Method in class org.encog.neural.networks.logic.ART1Logic
HiddenLayerParams - Class in org.encog.neural.prune: Specifies the minimum and maximum neuron counts for a layer.
HiddenLayerParams(int, int) - Constructor for class org.encog.neural.prune.HiddenLayerParams: Construct a hidden layer param object with the specified min and max values.
HopfieldLogic - Class in org.encog.neural.networks.logic: Provides the neural logic for an Hopfield type network.
HopfieldLogic() - Constructor for class org.encog.neural.networks.logic.HopfieldLogic
HopfieldPattern - Class in org.encog.neural.pattern: Create a Hopfield pattern.
HopfieldPattern() - Constructor for class org.encog.neural.pattern.HopfieldPattern
HOURS_DAY - Static variable in class org.encog.util.time.TimeSpan: Hours in a day.
HybridStrategy - Class in org.encog.neural.networks.training.strategy: A hybrid stragey allows a secondary training algorithm to be used.
HybridStrategy(Train) - Constructor for class org.encog.neural.networks.training.strategy.HybridStrategy: Construct a hybrid strategy with the default minimum improvement and toleration cycles.
HybridStrategy(Train, double, int, int) - Constructor for class org.encog.neural.networks.training.strategy.HybridStrategy: Create a hybrid strategy.
hypot(double, double) - Static method in class org.encog.util.math.EncogMath: sqrt(a^2 + b^2) without under/overflow.

I

identity(int) - Static method in class org.encog.matrix.MatrixMath: Return an identity matrix of the specified size.
ImageNeuralData - Class in org.encog.neural.data.image: An extension of the BasicNeuralData class that is designed to hold images for input into a neural network.
ImageNeuralData(Image) - Constructor for class org.encog.neural.data.image.ImageNeuralData: Construct an object based on an image.
ImageNeuralDataSet - Class in org.encog.neural.data.image: Store a collection of images for training with a neural network.
ImageNeuralDataSet(Downsample, boolean, double, double) - Constructor for class org.encog.neural.data.image.ImageNeuralDataSet: Construct this class with the specified downsampler.
ImageSize - Class in org.encog.util: Simple class to determine the size of an image.
ImageSize(Image) - Constructor for class org.encog.util.ImageSize: Determine the size of an image.
imageUpdate(Image, int, int, int, int, int) - Method in class org.encog.util.ImageSize: The image has been updated.
INC_Y - Static variable in class org.encog.neural.pattern.PatternConst: How much to increase y by as the network grows.
INDENT_X - Static variable in class org.encog.neural.pattern.PatternConst: How much to indent on the x-axis.
INDEX_FILE - Static variable in class org.encog.util.http.URLUtility: The name of the usual default document.
Indexable - Interface in org.encog.neural.data: Specifies that a data set can be accessed in random order via an index.
IndexRangeSegregator - Class in org.encog.normalize.segregate.index: An index segregator is used to segregate the data according to its index.
IndexRangeSegregator() - Constructor for class org.encog.normalize.segregate.index.IndexRangeSegregator: Default constructor for reflection.
IndexRangeSegregator(int, int) - Constructor for class org.encog.normalize.segregate.index.IndexRangeSegregator: Construct an index range segregator.
IndexSampleSegregator - Class in org.encog.normalize.segregate.index: An index segregator is used to segregate the data according to its index.
IndexSampleSegregator() - Constructor for class org.encog.normalize.segregate.index.IndexSampleSegregator: The default constructor, for reflection.
IndexSampleSegregator(int, int, int) - Constructor for class org.encog.normalize.segregate.index.IndexSampleSegregator: Construct an index sample segregator.
IndexSegregator - Class in org.encog.normalize.segregate.index: The index segregator.
IndexSegregator() - Constructor for class org.encog.normalize.segregate.index.IndexSegregator
init(BasicNetwork) - Method in class org.encog.neural.networks.logic.ART1Logic: Setup the network logic, read parameters from the network.
init(BasicNetwork) - Method in class org.encog.neural.networks.logic.ARTLogic: Setup the network logic, read parameters from the network.
init(BasicNetwork) - Method in class org.encog.neural.networks.logic.BAMLogic: Setup the network logic, read parameters from the network.
init(BasicNetwork) - Method in class org.encog.neural.networks.logic.BoltzmannLogic: Setup the network logic, read parameters from the network.
init(BasicNetwork) - Method in class org.encog.neural.networks.logic.FeedforwardLogic: Setup the network logic, read parameters from the network.
init(BasicNetwork) - Method in interface org.encog.neural.networks.logic.NeuralLogic: Setup the network logic, read parameters from the network.
init(BasicNetwork) - Method in class org.encog.neural.networks.logic.ThermalLogic: Setup the network logic, read parameters from the network.
init(Train) - Method in class org.encog.neural.networks.training.strategy.Greedy: Initialize this strategy.
init(Train) - Method in class org.encog.neural.networks.training.strategy.HybridStrategy: Initialize this strategy.
init(Train) - Method in interface org.encog.neural.networks.training.Strategy: Initialize this strategy.
init(Train) - Method in class org.encog.neural.networks.training.strategy.ResetStrategy: Initialize this strategy.
init(Train) - Method in class org.encog.neural.networks.training.strategy.SmartLearningRate: Initialize this strategy.
init(Train) - Method in class org.encog.neural.networks.training.strategy.SmartMomentum: Initialize this strategy.
init(Train) - Method in class org.encog.neural.networks.training.strategy.StopTrainingStrategy: Initialize this strategy.
init(DataNormalization) - Method in class org.encog.normalize.segregate.index.IndexSegregator: Setup this class with the specified normalization object.
init(DataNormalization) - Method in class org.encog.normalize.segregate.IntegerBalanceSegregator: Init the segregator with the owning normalization object.
init(DataNormalization) - Method in class org.encog.normalize.segregate.RangeSegregator: Init the object.
init(DataNormalization) - Method in interface org.encog.normalize.segregate.Segregator: Setup this object to use the specified normalization object.
initForOutput() - Method in class org.encog.normalize.DataNormalization: Setup the row for output.
initForPass() - Method in class org.encog.normalize.DataNormalization: Setup the row for output.
initGenes(int) - Method in class org.encog.neural.networks.training.genetic.NeuralChromosome: Init the genes array.
INITIAL_DEPTH - Static variable in class org.encog.parse.PeekableInputStream: The depth to peek.
Input - Class in org.encog.bot.browse.range: A form element that represents for input for text.
Input(WebPage) - Constructor for class org.encog.bot.browse.range.Input: Construct this Input element.
InputField - Interface in org.encog.normalize.input: A Normalization input field.
InputFieldArray1D - Class in org.encog.normalize.input: An input field that comes from a 1D array.
InputFieldArray1D(boolean, double[]) - Constructor for class org.encog.normalize.input.InputFieldArray1D: Construct the 1D array field.
InputFieldArray2D - Class in org.encog.normalize.input: An input field that comes from a 2D array.
InputFieldArray2D(boolean, double[][], int) - Constructor for class org.encog.normalize.input.InputFieldArray2D: Construct a 2D array input field.
InputFieldCSV - Class in org.encog.normalize.input: An input field based on a CSV file.
InputFieldCSV() - Constructor for class org.encog.normalize.input.InputFieldCSV: Construct an InputFieldCSV with the default constructor.
InputFieldCSV(boolean, File, int) - Constructor for class org.encog.normalize.input.InputFieldCSV: Construct a input field for a CSV file.
InputFieldNeuralDataSet - Class in org.encog.normalize.input: An input field based on an Encog NeuralDataSet.
InputFieldNeuralDataSet(boolean, NeuralDataSet, int) - Constructor for class org.encog.normalize.input.InputFieldNeuralDataSet: Construct a input field based on a NeuralDataSet.
InputStreamPersistence - Class in org.encog.persist.location: This class allows Encog persistence to use a location that is based on an InputStream.
InputStreamPersistence(InputStream) - Constructor for class org.encog.persist.location.InputStreamPersistence: Construct this location.
inRange(double) - Method in class org.encog.normalize.output.mapped.MappedRange: Determine if the specified value is in the range.
inRange(double) - Method in class org.encog.normalize.segregate.SegregationRange: Is this value within the range.
IntegerBalanceSegregator - Class in org.encog.normalize.segregate: Balance based on an input value.
IntegerBalanceSegregator(InputField, int) - Constructor for class org.encog.normalize.segregate.IntegerBalanceSegregator: Construct an integer balance segregator.
IntegerBalanceSegregator() - Constructor for class org.encog.normalize.segregate.IntegerBalanceSegregator: Default constructor.
inverse() - Method in class org.encog.matrix.Matrix
is(String, boolean) - Method in class org.encog.parse.tags.read.ReadTags: Checks to see if the next tag is the tag specified.
isAutoSend() - Method in class org.encog.bot.browse.range.FormElement
isAutoSend() - Method in class org.encog.bot.browse.range.Input
isCloseConnection() - Method in class org.encog.neural.data.sql.SQLNeuralDataSet
isConnectedTo(Layer) - Method in class org.encog.neural.networks.layers.BasicLayer: Determine if this layer is connected to another layer.
isConnectedTo(Layer) - Method in interface org.encog.neural.networks.layers.Layer: Determine if this layer is connected to another.
isDefined(String) - Method in class org.encog.neural.data.PropertyData: Determine of the specified property is defined.
isForceWinner() - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining
isFullRank() - Method in class org.encog.matrix.decomposition.QRDecomposition: Is the matrix full rank?
isIdeal() - Method in class org.encog.normalize.output.BasicOutputField
isIdeal() - Method in interface org.encog.normalize.output.OutputField
isIncluded() - Method in class org.encog.normalize.segregate.SegregationRange
isInput() - Method in class org.encog.neural.data.temporal.TemporalDataDescription
isInRange() - Method in class org.encog.normalize.output.nominal.NominalItem
isInstanceOf(Class<?>, Class<?>) - Static method in class org.encog.util.ReflectionUtil: Determine if one class is an instance of the other class.
isNonsingular() - Method in class org.encog.matrix.decomposition.LUDecomposition: Is the matrix nonsingular?
isPointInRange(TemporalPoint) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Is the specified point within the range.
isPredict() - Method in class org.encog.neural.data.temporal.TemporalDataDescription
isPreventRepeat() - Method in class org.encog.solve.genetic.GeneticAlgorithm: Should repeating genes be prevented.
isPrimitive(Object) - Static method in class org.encog.util.ReflectionUtil: Determine if the specified object is a primitive.
isSelfConnected() - Method in class org.encog.neural.networks.layers.BasicLayer
isSelfConnected() - Method in class org.encog.neural.networks.synapse.BasicSynapse
isSelfConnected() - Method in interface org.encog.neural.networks.synapse.Synapse
isShouldMinimize() - Method in class org.encog.solve.anneal.SimulatedAnnealing
isSimple(Object) - Static method in class org.encog.util.ReflectionUtil: Determine if an object is "simple", that is it should be persisted just with a .tostring.
isSPD() - Method in class org.encog.matrix.decomposition.CholeskyDecomposition: Is the matrix symmetric and positive definite?
isSupervised() - Method in class org.encog.neural.data.basic.BasicNeuralDataPair: Determine if this data pair is supervised.
isSupervised() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Determine if this neural data set is supervied.
isSupervised() - Method in interface org.encog.neural.data.NeuralDataPair
isTeachable() - Method in class org.encog.neural.networks.synapse.DirectSynapse
isTeachable() - Method in class org.encog.neural.networks.synapse.OneToOneSynapse
isTeachable() - Method in interface org.encog.neural.networks.synapse.Synapse
isTeachable() - Method in class org.encog.neural.networks.synapse.WeightedSynapse
isTeachable() - Method in class org.encog.neural.networks.synapse.WeightlessSynapse
isValidResume(TrainingContinuation) - Method in class org.encog.neural.networks.training.propagation.Propagation: Determine if this specified training continuation object is valid for this training method.
isValidResume(TrainingContinuation) - Method in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation: Determine if the specified continuation object is valid to resume with.
isVector() - Method in class org.encog.matrix.Matrix: Determine if the matrix is a vector.
isZero() - Method in class org.encog.matrix.Matrix: Return true if every value in the matrix is zero.
iteration() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing: Perform one iteration of simulated annealing.
iteration() - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining: Perform one training iteration.
iteration() - Method in class org.encog.neural.networks.training.cpn.TrainInstar: Perform one training iteration.
iteration() - Method in class org.encog.neural.networks.training.cpn.TrainOutstar: Perform one training iteration.
iteration() - Method in class org.encog.neural.networks.training.genetic.NeuralGeneticAlgorithm: Perform one training iteration.
iteration() - Method in class org.encog.neural.networks.training.propagation.Propagation: Perform one training iteration.
iteration() - Method in class org.encog.neural.networks.training.propagation.scg.ScaledConjugateGradient: Perform one iteration.
iteration() - Method in class org.encog.neural.networks.training.simple.TrainAdaline: Perform a training iteration.
iteration() - Method in interface org.encog.neural.networks.training.Train: Perform one iteration of training.
iteration() - Method in class org.encog.solve.anneal.SimulatedAnnealing: Called to perform one cycle of the annealing process.
iteration() - Method in class org.encog.solve.genetic.GeneticAlgorithm: Modify the weight matrix and thresholds based on the last call to calcError.
iterator() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Create an iterator for this collection.
iterator() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet
iterator() - Method in class org.encog.neural.data.csv.CSVNeuralDataSet: Get an iterator to use with the CSV data.
iterator() - Method in class org.encog.neural.data.sql.SQLNeuralDataSet: Get an iterator for this collection.
iterator() - Method in class org.encog.neural.data.union.UnionNeuralDataSet: Obtain an iterator to access the collection of data.
iterator() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet

J

JobUnitContext - Class in org.encog.util.concurrency.job: The job unit context contains context information to be passed to a job unit.
JobUnitContext() - Constructor for class org.encog.util.concurrency.job.JobUnitContext
JobUnitWorker - Class in org.encog.util.concurrency.job: An individual worker, that will be submitted to the thread pool.
JobUnitWorker(JobUnitContext) - Constructor for class org.encog.util.concurrency.job.JobUnitWorker: Construct a job unit.
JordanPattern - Class in org.encog.neural.pattern: This class is used to generate an Jordan style recurrent neural network.
JordanPattern() - Constructor for class org.encog.neural.pattern.JordanPattern: Construct an object to create a Jordan type neural network.

L

LAST_GRADIENTS - Static variable in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation: Continuation tag for the last gradients.
Layer - Interface in org.encog.neural.networks.layers: This interface defines all necessary methods for a neural network layer.
LayerComparator - Class in org.encog.neural.networks.structure: Used to compare layers and ensure a consistent sort order.
LayerComparator(NeuralStructure) - Constructor for class org.encog.neural.networks.structure.LayerComparator: Construct a level comparator for the specified structure.
LEARNING_DECAY - Static variable in class org.encog.neural.networks.training.strategy.SmartLearningRate: Learning decay rate.
LearningRate - Interface in org.encog.neural.networks.training: Specifies that a training algorithm has the concept of a learning rate.
length() - Method in interface org.encog.normalize.input.HasFixedLength
length() - Method in class org.encog.normalize.input.InputFieldArray1D
length() - Method in class org.encog.normalize.input.InputFieldArray2D
LinearCongruentialGenerator - Class in org.encog.util.math: A predictable random number generator.
LinearCongruentialGenerator(long) - Constructor for class org.encog.util.math.LinearCongruentialGenerator: Construct the default LCG.
LinearCongruentialGenerator(long, long, long, long) - Constructor for class org.encog.util.math.LinearCongruentialGenerator: Create a LCG with the specified modulus, multiplier and increment.
Link - Class in org.encog.bot.browse.range: A document range that represents a hyperlink, and any embedded tags and text.
Link(WebPage) - Constructor for class org.encog.bot.browse.range.Link: Construct a link from the specified web page.
load(InputStream) - Method in class org.encog.bot.browse.LoadWebPage: Load a web page from the specified stream.
load(String) - Method in class org.encog.bot.browse.LoadWebPage: Load the web page from a string that contains HTML.
load(URL) - Method in class org.encog.bot.rss.RSS: Load all RSS data from the specified URL.
load(Node) - Method in class org.encog.bot.rss.RSSItem: Load an item from the specified node.
load(NeuralDataSet) - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet: Load from the specified data source into the binary file.
load(TickerSymbol, Set<MarketDataType>, Date, Date) - Method in interface org.encog.neural.data.market.loader.MarketLoader: Load the specified ticker symbol for the specified date.
load(TickerSymbol, Set<MarketDataType>, Date, Date) - Method in class org.encog.neural.data.market.loader.YahooFinanceLoader: Load the specified financial data.
load(Date, Date) - Method in class org.encog.neural.data.market.MarketNeuralDataSet: Load data from the loader.
load(PersistenceLocation) - Method in class org.encog.persist.EncogMemoryCollection: Load the contents of a location.
load(ReadXML) - Method in interface org.encog.persist.Persistor: Load from the specified node.
load(ReadXML) - Method in class org.encog.persist.persistors.ActivationBiPolarPersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.ActivationCompetitivePersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.ActivationGaussianPersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.ActivationLinearPersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.ActivationLOGPersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.ActivationSigmoidPersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.ActivationSINPersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.ActivationSoftMaxPersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.ActivationTANHPersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.BasicLayerPersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.BasicNetworkPersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.BasicNeuralDataSetPersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.ContextLayerPersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.DirectSynapsePersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.generic.GenericPersistor: Load from the specified node.
load(ReadXML, EncogPersistedObject) - Method in class org.encog.persist.persistors.generic.XML2Object: Load an object from XML.
load(ReadXML) - Method in class org.encog.persist.persistors.OneToOneSynapsePersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.PropertyDataPersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.RadialBasisFunctionLayerPersistor: Load a RBF layer.
load(ReadXML) - Method in class org.encog.persist.persistors.TextDataPersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.TrainingContinuationPersistor: Load the object.
load(ReadXML) - Method in class org.encog.persist.persistors.WeightedSynapsePersistor: Load the specified Encog object from an XML reader.
load(ReadXML) - Method in class org.encog.persist.persistors.WeightlessSynapsePersistor: Load the specified Encog object from an XML reader.
load(String) - Static method in class org.encog.util.SerializeObject: Load an object.
loadClassmap() - Static method in class org.encog.util.ReflectionUtil: Load the classmap file.
loadContents() - Method in class org.encog.bot.browse.LoadWebPage: Using the data units, which should have already been loaded by this time, load the contents of the web page.
loadCookies(URLConnection) - Method in class org.encog.util.http.CookieUtility: Load any cookies from the specified URLConnection object.
loadDataUnits(InputStream) - Method in class org.encog.bot.browse.LoadWebPage: Load the data units.
LoadedMarketData - Class in org.encog.neural.data.market.loader: This class contains market data that was loaded for a specific ticker symbol and a specific date.
LoadedMarketData(Date, TickerSymbol) - Constructor for class org.encog.neural.data.market.loader.LoadedMarketData: Construct one sample of market data.
LoaderError - Exception in org.encog.neural.data.market.loader: An error that occurs when financial data is being loaded.
LoaderError(String) - Constructor for exception org.encog.neural.data.market.loader.LoaderError: Construct a message exception.
LoaderError(Throwable) - Constructor for exception org.encog.neural.data.market.loader.LoaderError: Construct an exception that holds another exception.
loadForm(int, Tag) - Method in class org.encog.bot.browse.LoadWebPage: Called by loadContents to load a form on the page.
loadInput(int, Tag) - Method in class org.encog.bot.browse.LoadWebPage: Called by loadContents to load an input tag on the form.
loadLink(int, Tag) - Method in class org.encog.bot.browse.LoadWebPage: Called by loadContents to load a link on the page.
loadMatrix(ReadXML) - Static method in class org.encog.persist.persistors.PersistorUtil: Load a matrix from the reader.
loadPage(InputStream) - Static method in class org.encog.bot.BotUtil: Load load from the specified input stream.
loadPage(URL) - Static method in class org.encog.bot.BotUtil: Load the specified web page into a string.
loadTitle(int, Tag) - Method in class org.encog.bot.browse.LoadWebPage: Called by loadContents to load the title of the page.
LoadWebPage - Class in org.encog.bot.browse: Called to actually load a web page.
LoadWebPage(URL) - Constructor for class org.encog.bot.browse.LoadWebPage: Construct a web page loader with the specified base URL.
loadWorkload() - Method in class org.encog.neural.prune.PruneIncremental: Get the next workload.
loadWorkload() - Method in class org.encog.util.concurrency.job.ConcurrentJob: Load the subtasks.
log(double) - Static method in class org.encog.util.math.BoundMath: Calculate the log.
Logging - Class in org.encog.util.logging: Provides simple logging access to the JDK logging system.
LUDecomposition - Class in org.encog.matrix.decomposition: LU Decomposition.
LUDecomposition(Matrix) - Constructor for class org.encog.matrix.decomposition.LUDecomposition: LU Decomposition

M

magnitude(BiPolarNeuralData) - Method in class org.encog.neural.networks.logic.ART1Logic: Get the magnitude of the specified input.
main(String[]) - Static method in class org.encog.util.GenerateClasslist: Run the utility.
ManhattanPropagation - Class in org.encog.neural.networks.training.propagation.manhattan: One problem that the backpropagation technique has is that the magnitude of the partial derivative may be calculated too large or too small.
ManhattanPropagation(BasicNetwork, NeuralDataSet, double) - Constructor for class org.encog.neural.networks.training.propagation.manhattan.ManhattanPropagation: Construct a class to train with Manhattan propagation.
ManhattanPropagation(BasicNetwork, NeuralDataSet, double, double) - Constructor for class org.encog.neural.networks.training.propagation.manhattan.ManhattanPropagation: Construct a Manhattan propagation training object.
MappedRange - Class in org.encog.normalize.output.mapped: Simple class that is used internally to hold a range mapping.
MappedRange(double, double, double) - Constructor for class org.encog.normalize.output.mapped.MappedRange: Construct the range mapping.
MarketDataDescription - Class in org.encog.neural.data.market: This class is used to describe the type of financial data that is needed.
MarketDataDescription(TickerSymbol, MarketDataType, ActivationFunction, boolean, boolean) - Constructor for class org.encog.neural.data.market.MarketDataDescription: Construct a MarketDataDescription item.
MarketDataDescription(TickerSymbol, MarketDataType, boolean, boolean) - Constructor for class org.encog.neural.data.market.MarketDataDescription: Construct a MarketDataDescription item.
MarketDataType - Enum in org.encog.neural.data.market: The types of market data that can be used.
MarketError - Exception in org.encog.neural.data.market: Thrown when an error occurs processing market data.
MarketError(String) - Constructor for exception org.encog.neural.data.market.MarketError: Construct a message exception.
MarketError(Throwable) - Constructor for exception org.encog.neural.data.market.MarketError: Construct an exception that holds another exception.
MarketLoader - Interface in org.encog.neural.data.market.loader: This interface defines a class that can be used to load external financial data.
MarketNeuralDataSet - Class in org.encog.neural.data.market: A data set that is designed to hold market data.
MarketNeuralDataSet(MarketLoader, int, int) - Constructor for class org.encog.neural.data.market.MarketNeuralDataSet: Construct a market data set object.
MarketPoint - Class in org.encog.neural.data.market: Hold one market datapoint.
MarketPoint(Date, int) - Constructor for class org.encog.neural.data.market.MarketPoint: Construct a MarketPoint with the specified date and size.
mate(Chromosome<GENE_TYPE>, Chromosome<GENE_TYPE>, Chromosome<GENE_TYPE>) - Method in class org.encog.solve.genetic.Chromosome: Assuming this chromosome is the "mother" mate with the passed in "father".
MateWorker<GENE_TYPE> - Class in org.encog.solve.genetic: This class is used in conjunction with a thread pool.
MateWorker(Chromosome<GENE_TYPE>, Chromosome<GENE_TYPE>, Chromosome<GENE_TYPE>, Chromosome<GENE_TYPE>) - Constructor for class org.encog.solve.genetic.MateWorker
MathConst - Class in org.encog.util.math: Math constants needed by Encog.
Matrix - Class in org.encog.matrix: This class implements a mathematical matrix.
Matrix(boolean[][]) - Constructor for class org.encog.matrix.Matrix: Construct a bipolar matrix from an array of booleans.
Matrix(double[][]) - Constructor for class org.encog.matrix.Matrix: Create a matrix from an array of doubles.
Matrix(int, int) - Constructor for class org.encog.matrix.Matrix: Create a blank array with the specified number of rows and columns.
MatrixError - Exception in org.encog.matrix: Used by the matrix classes to indicate an error.
MatrixError(String) - Constructor for exception org.encog.matrix.MatrixError: Construct this exception with a message.
MatrixError(Throwable) - Constructor for exception org.encog.matrix.MatrixError: Construct this exception with another exception.
MatrixMath - Class in org.encog.matrix: This class can perform many different mathematical operations on matrixes.
MAX_LENGTH - Static variable in class org.encog.parse.tags.read.ReadTags: Maximum length string to read.
MAX_MOMENTUM - Static variable in class org.encog.neural.networks.training.strategy.SmartMomentum: The maximum value that momentum can go to.
MAX_PRECIS - Static variable in class org.encog.util.logging.DumpMatrix: Maximum precision.
MAX_RAND - Static variable in class org.encog.util.math.LinearCongruentialGenerator: The maximum rand number that the standard GCC based LCG will generate.
mergeObjects(PersistenceLocation, String) - Method in class org.encog.persist.PersistWriter: Merge the objects from this collection into the new one.
mergeTemp() - Method in class org.encog.persist.EncogPersistedCollection: Merge the temp file with the main one, call this to make any changes permanent.
MILIS - Static variable in class org.encog.util.benchmark.Evaluate: Mili-seconds in a second.
MIN_IMPROVEMENT - Static variable in class org.encog.neural.networks.training.strategy.SmartMomentum: The minimum improvement to adjust momentum.
MINUTES_HOUR - Static variable in class org.encog.util.time.TimeSpan: Minutes in an hour.
modifyObject(PersistenceLocation, String, String, String) - Method in class org.encog.persist.PersistWriter: Modify the specified object, such as changing its name or description.
Momentum - Interface in org.encog.neural.networks.training: Specifies that a training algorithm has the concept of a momentum.
MOMENTUM_CYCLES - Static variable in class org.encog.neural.networks.training.strategy.SmartMomentum: How many cycles to accept before adjusting momentum.
MOMENTUM_INCREASE - Static variable in class org.encog.neural.networks.training.strategy.SmartMomentum: How much to increase momentum by.
MONTHS_YEAR - Static variable in class org.encog.util.time.TimeSpan: Months in a year.
MultiplicativeGroup - Class in org.encog.normalize.output.multiplicative: Used to group multiplicative fields together.
MultiplicativeGroup() - Constructor for class org.encog.normalize.output.multiplicative.MultiplicativeGroup
multiply(double) - Method in class org.encog.matrix.Matrix: Multiply every value in the matrix by the specified value.
multiply(double[], double[]) - Method in class org.encog.matrix.Matrix: Multiply every row by the specified vector.
multiply(Matrix, double) - Static method in class org.encog.matrix.MatrixMath: Return the result of multiplying every cell in the matrix by the specified value.
multiply(Matrix, Matrix) - Static method in class org.encog.matrix.MatrixMath: Return the product of the first and second matrix.
MUST_USE_IMAGE - Static variable in class org.encog.neural.data.image.ImageNeuralDataSet: Error message to inform the caller that only ImageNeuralData objects can be used with this collection.
mutate() - Method in class org.encog.neural.networks.training.genetic.NeuralChromosome: Mutate this chromosome randomly.
mutate() - Method in class org.encog.solve.genetic.Chromosome: Called to mutate this chromosome.

N

nameLayer(Layer) - Method in class org.encog.neural.networks.structure.NeuralStructure: Obtain a name for the specified layer.
navigate(Form) - Method in class org.encog.bot.browse.Browser: Navigate to the specified form by performing a submit of that form.
navigate(Form, Input) - Method in class org.encog.bot.browse.Browser: Navigate based on a form.
navigate(Link) - Method in class org.encog.bot.browse.Browser: Navigate to a new page based on a link.
navigate(String) - Method in class org.encog.bot.browse.Browser: Navigate based on a string URL.
navigate(URL) - Method in class org.encog.bot.browse.Browser: Navigate to a page based on a URL object.
navigate(URL, InputStream) - Method in class org.encog.bot.browse.Browser: Navigate to a page and post the specified data.
NEGATIVE_ETA - Static variable in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation: The NEGATIVE ETA value.
NeighborhoodBubble - Class in org.encog.neural.networks.training.competitive.neighborhood: A neighborhood function that uses a simple bubble.
NeighborhoodBubble(int) - Constructor for class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodBubble: Create a bubble neighborhood function that will return 1.0 (full update) for any neuron that is plus or minus the width distance from the winning neuron.
NeighborhoodFunction - Interface in org.encog.neural.networks.training.competitive.neighborhood: Defines how a neighborhood function should work in competitive training.
NeighborhoodGaussian - Class in org.encog.neural.networks.training.competitive.neighborhood: A neighborhood function based on the Gaussian function.
NeighborhoodGaussian(RadialBasisFunction) - Constructor for class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodGaussian: Construct the neighborhood function with the specified radial function.
NeighborhoodGaussianMulti - Class in org.encog.neural.networks.training.competitive.neighborhood: Implements a multi-dimensional gaussian neighborhood function.
NeighborhoodGaussianMulti(int, int) - Constructor for class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodGaussianMulti: Construct a 2d neighborhood function based on the sizes for the x and y dimensions.
NeighborhoodSingle - Class in org.encog.neural.networks.training.competitive.neighborhood: A very simple neighborhood function that will return 1.0 (full effect) for the winning neuron, and 0.0 (no change) for everything else.
NeighborhoodSingle() - Constructor for class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodSingle
Network - Interface in org.encog.neural.networks: Interface that defines a neural network.
NetworkCODEC - Class in org.encog.neural.networks.structure: This class will extract the "long term memory" of a neural network, that is the weights and threshold values into an array.
NetworkPattern - Enum in org.encog.neural.prune: Specify which network pattern to use.
networkToArray(BasicNetwork) - Static method in class org.encog.neural.networks.structure.NetworkCODEC: Convert to an array.
networkToString(BasicNetwork) - Static method in class org.encog.neural.prune.PruneIncremental: Format the network as a human readable string that lists the hidden layers.
NeuralChromosome - Class in org.encog.neural.networks.training.genetic: Implements a chromosome that allows a feedforward neural network to be trained using a genetic algorithm.
NeuralChromosome(NeuralGeneticAlgorithm, BasicNetwork) - Constructor for class org.encog.neural.networks.training.genetic.NeuralChromosome: Construct a neural chromosome.
NeuralData - Interface in org.encog.neural.data: Defines an array of data.
NeuralDataError - Exception in org.encog.neural.data: Used by the neural network classes to indicate an error.
NeuralDataError(String) - Constructor for exception org.encog.neural.data.NeuralDataError: Construct a message exception.
NeuralDataError(Throwable) - Constructor for exception org.encog.neural.data.NeuralDataError: Construct an exception that holds another exception.
NeuralDataFieldHolder - Class in org.encog.normalize.input: Simple holder class used internally for Encog.
NeuralDataFieldHolder(Iterator<NeuralDataPair>, InputFieldNeuralDataSet) - Constructor for class org.encog.normalize.input.NeuralDataFieldHolder: Construct the class.
NeuralDataMapping - Class in org.encog.neural.networks: Used to map one neural data object to another.
NeuralDataMapping() - Constructor for class org.encog.neural.networks.NeuralDataMapping: Construct the neural data mapping class, with null values.
NeuralDataMapping(NeuralData, NeuralData) - Constructor for class org.encog.neural.networks.NeuralDataMapping: Construct the neural data mapping class with the specified values.
NeuralDataPair - Interface in org.encog.neural.data: Training data is stored in two ways, depending on if the data is for supervised, or unsupervised training.
NeuralDataSet - Interface in org.encog.neural.data: An interface designed to abstract classes that store neural data.
NeuralGeneticAlgorithm - Class in org.encog.neural.networks.training.genetic: Implements a genetic algorithm that allows a feedforward or simple recurrent neural network to be trained using a genetic algorithm.
NeuralGeneticAlgorithm(BasicNetwork, Randomizer, CalculateScore, int, double, double) - Constructor for class org.encog.neural.networks.training.genetic.NeuralGeneticAlgorithm: Construct a neural genetic algorithm.
NeuralGeneticAlgorithm.NeuralGeneticAlgorithmHelper - Class in org.encog.neural.networks.training.genetic: Very simple class that implements a genetic algorithm.
NeuralGeneticAlgorithm.NeuralGeneticAlgorithmHelper() - Constructor for class org.encog.neural.networks.training.genetic.NeuralGeneticAlgorithm.NeuralGeneticAlgorithmHelper
NeuralLogic - Interface in org.encog.neural.networks.logic: Neural logic classes implement neural network logic for a variety of neural network setups.
NeuralNetworkError - Exception in org.encog.neural: Used by the neural network classes to indicate an error.
NeuralNetworkError(String) - Constructor for exception org.encog.neural.NeuralNetworkError: Construct a message exception.
NeuralNetworkError(Throwable) - Constructor for exception org.encog.neural.NeuralNetworkError: Construct an exception that holds another exception.
NeuralNetworkError(String, Throwable) - Constructor for exception org.encog.neural.NeuralNetworkError: Construct an exception that holds another exception.
NeuralNetworkPattern - Interface in org.encog.neural.pattern: Patterns are used to create common sorts of neural networks.
NeuralOutputHolder - Class in org.encog.neural.networks: Holds the output from each layer of the neural network.
NeuralOutputHolder() - Constructor for class org.encog.neural.networks.NeuralOutputHolder: Construct an empty holder.
NeuralSimulatedAnnealing - Class in org.encog.neural.networks.training.anneal: This class implements a simulated annealing training algorithm for neural networks.
NeuralSimulatedAnnealing(BasicNetwork, CalculateScore, double, double, int) - Constructor for class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing: Construct a simulated annleaing trainer for a feedforward neural network.
NeuralSimulatedAnnealingHelper - Class in org.encog.neural.networks.training.anneal: Simple class used by the neural simulated annealing.
NeuralSimulatedAnnealingHelper(NeuralSimulatedAnnealing) - Constructor for class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealingHelper: Constructs this object.
NeuralStructure - Class in org.encog.neural.networks.structure: Holds "cached" information about the structure of the neural network.
NeuralStructure(BasicNetwork) - Constructor for class org.encog.neural.networks.structure.NeuralStructure: Construct a structure object for the specified network.
next() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet.BasicNeuralIterator: Read the next item.
next() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet.BufferedNeuralDataSetIterator
next() - Method in class org.encog.neural.data.csv.CSVNeuralDataSet.CSVNeuralIterator: Read the next record from the CSV file.
next() - Method in class org.encog.neural.data.sql.SQLNeuralDataSet.SQLNeuralIterator: Read the next row from the database.
next() - Method in class org.encog.neural.data.union.UnionNeuralDataSet.UnionIterator: Obtain the next piece of data.
next() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet.XMLNeuralIterator: Read the next training set item.
next() - Method in class org.encog.util.csv.ReadCSV: Read the next line.
nextDouble() - Method in class org.encog.util.math.LinearCongruentialGenerator
nextLong() - Method in class org.encog.util.math.LinearCongruentialGenerator
NominalItem - Class in org.encog.normalize.output.nominal: A nominal item.
NominalItem() - Constructor for class org.encog.normalize.output.nominal.NominalItem: Construct a empty range item.
NominalItem(InputField, double, double) - Constructor for class org.encog.normalize.output.nominal.NominalItem: Create a nominal item.
norm2() - Method in class org.encog.matrix.decomposition.SingularValueDecomposition: Two norm
NormalizationError - Exception in org.encog.normalize: Used for normalization errors.
NormalizationError(String) - Constructor for exception org.encog.normalize.NormalizationError: Construct a message exception.
NormalizationError(Throwable) - Constructor for exception org.encog.normalize.NormalizationError: Construct an exception that holds another exception.
NormalizationStorage - Interface in org.encog.normalize.target: Defines a means by which normalized data can be stored.
NormalizationStorageArray1D - Class in org.encog.normalize.target: Output the normalized data to a 1D array.
NormalizationStorageArray1D(double[]) - Constructor for class org.encog.normalize.target.NormalizationStorageArray1D: Construct an object to store to a 2D array.
NormalizationStorageArray2D - Class in org.encog.normalize.target: Output the normalized data to a 2D array.
NormalizationStorageArray2D(double[][]) - Constructor for class org.encog.normalize.target.NormalizationStorageArray2D: Construct an object to store to a 2D array.
NormalizationStorageCSV - Class in org.encog.normalize.target: Store normalized data to a CSV file.
NormalizationStorageCSV(CSVFormat, File) - Constructor for class org.encog.normalize.target.NormalizationStorageCSV: Construct a CSV storage object from the specified file.
NormalizationStorageCSV(File) - Constructor for class org.encog.normalize.target.NormalizationStorageCSV: Construct a CSV storage object from the specified file.
NormalizationStorageNeuralDataSet - Class in org.encog.normalize.target: Store the normalized data to a neural data set.
NormalizationStorageNeuralDataSet(int, int) - Constructor for class org.encog.normalize.target.NormalizationStorageNeuralDataSet: Construct a new NeuralDataSet based on the parameters specified.
NormalizationStorageNeuralDataSet(NeuralDataSet) - Constructor for class org.encog.normalize.target.NormalizationStorageNeuralDataSet: Construct a normalized neural storage class to hold data.
normalizeBinary(double) - Static method in class org.encog.matrix.BiPolarUtil: Normalize a binary number.
NullStatusReportable - Class in org.encog: A report object that does nothing.
NullStatusReportable() - Constructor for class org.encog.NullStatusReportable
NumberList - Class in org.encog.util.csv: Class used to handle lists of numbers.

O

Object2XML - Class in org.encog.persist.persistors.generic: A generic class used to take an object and produce XML for it.
Object2XML() - Constructor for class org.encog.persist.persistors.generic.Object2XML
ObjectCloner - Class in org.encog.util: A simple Object cloner that uses serialization.
ObjectMapper - Class in org.encog.persist.persistors.generic: Used to map objects to reference numbers.
ObjectMapper() - Constructor for class org.encog.persist.persistors.generic.ObjectMapper
ObjectTagger - Class in org.encog.persist.persistors.generic: The object tagger is used in generic persistence to tag objects with a reference number.
ObjectTagger() - Constructor for class org.encog.persist.persistors.generic.ObjectTagger
objectToDouble(Double[]) - Static method in class org.encog.util.EncogArray: Convert an array of Double objects to double primitives.
obtainPair() - Method in class org.encog.normalize.input.NeuralDataFieldHolder: Obtain the next pair.
OneToOneSynapse - Class in org.encog.neural.networks.synapse: A one-to-one synapse requires that the from and to layers have exactly the same number of neurons.
OneToOneSynapse() - Constructor for class org.encog.neural.networks.synapse.OneToOneSynapse: Simple default constructor.
OneToOneSynapse(Layer, Layer) - Constructor for class org.encog.neural.networks.synapse.OneToOneSynapse: Construct a one-to-one synapse between the two layers.
OneToOneSynapsePersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the OneToOneSynapse class.
OneToOneSynapsePersistor() - Constructor for class org.encog.persist.persistors.OneToOneSynapsePersistor
open() - Method in interface org.encog.normalize.target.NormalizationStorage: Close the storage.
open() - Method in class org.encog.normalize.target.NormalizationStorageArray1D: Not needed for this storage type.
open() - Method in class org.encog.normalize.target.NormalizationStorageArray2D: Not needed for this storage type.
open() - Method in class org.encog.normalize.target.NormalizationStorageCSV: Open the CSV file.
open() - Method in class org.encog.normalize.target.NormalizationStorageNeuralDataSet: Not needed for this storage type.
openAdditional() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet: Create an additional data set.
openAdditional() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet: Open a second buffered data set, useful for multithreading.
openAdditional() - Method in interface org.encog.neural.data.Indexable: Opens an additional instance of this dataset.
org.encog - package org.encog
org.encog.bot - package org.encog.bot
org.encog.bot.browse - package org.encog.bot.browse
org.encog.bot.browse.range - package org.encog.bot.browse.range
org.encog.bot.dataunit - package org.encog.bot.dataunit
org.encog.bot.rss - package org.encog.bot.rss
org.encog.matrix - package org.encog.matrix
org.encog.matrix.decomposition - package org.encog.matrix.decomposition
org.encog.neural - package org.encog.neural
org.encog.neural.activation - package org.encog.neural.activation
org.encog.neural.data - package org.encog.neural.data
org.encog.neural.data.basic - package org.encog.neural.data.basic
org.encog.neural.data.bipolar - package org.encog.neural.data.bipolar
org.encog.neural.data.buffer - package org.encog.neural.data.buffer
org.encog.neural.data.csv - package org.encog.neural.data.csv
org.encog.neural.data.image - package org.encog.neural.data.image
org.encog.neural.data.market - package org.encog.neural.data.market
org.encog.neural.data.market.loader - package org.encog.neural.data.market.loader
org.encog.neural.data.sql - package org.encog.neural.data.sql
org.encog.neural.data.temporal - package org.encog.neural.data.temporal
org.encog.neural.data.union - package org.encog.neural.data.union
org.encog.neural.data.xml - package org.encog.neural.data.xml
org.encog.neural.networks - package org.encog.neural.networks
org.encog.neural.networks.layers - package org.encog.neural.networks.layers
org.encog.neural.networks.logic - package org.encog.neural.networks.logic
org.encog.neural.networks.structure - package org.encog.neural.networks.structure
org.encog.neural.networks.synapse - package org.encog.neural.networks.synapse
org.encog.neural.networks.training - package org.encog.neural.networks.training
org.encog.neural.networks.training.anneal - package org.encog.neural.networks.training.anneal
org.encog.neural.networks.training.competitive - package org.encog.neural.networks.training.competitive
org.encog.neural.networks.training.competitive.neighborhood - package org.encog.neural.networks.training.competitive.neighborhood
org.encog.neural.networks.training.cpn - package org.encog.neural.networks.training.cpn
org.encog.neural.networks.training.genetic - package org.encog.neural.networks.training.genetic
org.encog.neural.networks.training.propagation - package org.encog.neural.networks.training.propagation
org.encog.neural.networks.training.propagation.back - package org.encog.neural.networks.training.propagation.back
org.encog.neural.networks.training.propagation.gradient - package org.encog.neural.networks.training.propagation.gradient
org.encog.neural.networks.training.propagation.manhattan - package org.encog.neural.networks.training.propagation.manhattan
org.encog.neural.networks.training.propagation.resilient - package org.encog.neural.networks.training.propagation.resilient
org.encog.neural.networks.training.propagation.scg - package org.encog.neural.networks.training.propagation.scg
org.encog.neural.networks.training.simple - package org.encog.neural.networks.training.simple
org.encog.neural.networks.training.strategy - package org.encog.neural.networks.training.strategy
org.encog.neural.pattern - package org.encog.neural.pattern
org.encog.neural.prune - package org.encog.neural.prune
org.encog.normalize - package org.encog.normalize
org.encog.normalize.input - package org.encog.normalize.input
org.encog.normalize.output - package org.encog.normalize.output
org.encog.normalize.output.mapped - package org.encog.normalize.output.mapped
org.encog.normalize.output.multiplicative - package org.encog.normalize.output.multiplicative
org.encog.normalize.output.nominal - package org.encog.normalize.output.nominal
org.encog.normalize.output.zaxis - package org.encog.normalize.output.zaxis
org.encog.normalize.segregate - package org.encog.normalize.segregate
org.encog.normalize.segregate.index - package org.encog.normalize.segregate.index
org.encog.normalize.target - package org.encog.normalize.target
org.encog.parse - package org.encog.parse
org.encog.parse.tags - package org.encog.parse.tags
org.encog.parse.tags.read - package org.encog.parse.tags.read
org.encog.parse.tags.write - package org.encog.parse.tags.write
org.encog.persist - package org.encog.persist
org.encog.persist.annotations - package org.encog.persist.annotations
org.encog.persist.location - package org.encog.persist.location
org.encog.persist.persistors - package org.encog.persist.persistors
org.encog.persist.persistors.generic - package org.encog.persist.persistors.generic
org.encog.solve.anneal - package org.encog.solve.anneal
org.encog.solve.genetic - package org.encog.solve.genetic
org.encog.util - package org.encog.util
org.encog.util.benchmark - package org.encog.util.benchmark
org.encog.util.concurrency - package org.encog.util.concurrency
org.encog.util.concurrency.job - package org.encog.util.concurrency.job
org.encog.util.csv - package org.encog.util.csv
org.encog.util.downsample - package org.encog.util.downsample
org.encog.util.file - package org.encog.util.file
org.encog.util.http - package org.encog.util.http
org.encog.util.logging - package org.encog.util.logging
org.encog.util.math - package org.encog.util.math
org.encog.util.math.rbf - package org.encog.util.math.rbf
org.encog.util.randomize - package org.encog.util.randomize
org.encog.util.simple - package org.encog.util.simple
org.encog.util.time - package org.encog.util.time
OutputEquilateral - Class in org.encog.normalize.output.nominal: Allows nominal items to be encoded using the equilateral method.
OutputEquilateral() - Constructor for class org.encog.normalize.output.nominal.OutputEquilateral: Prodvide a default constructor for reflection.
OutputEquilateral(double, double) - Constructor for class org.encog.normalize.output.nominal.OutputEquilateral: Create an equilateral output field with the specified high and low output values.
OutputField - Interface in org.encog.normalize.output: An output field, this represents the actual output from the normalization.
OutputFieldDirect - Class in org.encog.normalize.output: A direct output field, will simply pass the input value to the output.
OutputFieldDirect(InputField) - Constructor for class org.encog.normalize.output.OutputFieldDirect: Construct a direct output field.
OutputFieldDirect() - Constructor for class org.encog.normalize.output.OutputFieldDirect: Default constructor, used for reflection.
OutputFieldEncode - Class in org.encog.normalize.output.mapped: An encoded output field.
OutputFieldEncode(InputField) - Constructor for class org.encog.normalize.output.mapped.OutputFieldEncode: Construct an encoded field.
OutputFieldGroup - Interface in org.encog.normalize.output: Output fields can be grouped together if they are calculated together.
OutputFieldGrouped - Class in org.encog.normalize.output: Defines an output field that can be grouped.
OutputFieldGrouped() - Constructor for class org.encog.normalize.output.OutputFieldGrouped: Default constructor, used mainly for reflection.
OutputFieldGrouped(OutputFieldGroup, InputField) - Constructor for class org.encog.normalize.output.OutputFieldGrouped: Construct a grouped output field.
OutputFieldMultiplicative - Class in org.encog.normalize.output.multiplicative: Both the multiplicative and z-axis normalization types allow a group of outputs to be adjusted so that the "vector length" is 1.
OutputFieldMultiplicative() - Constructor for class org.encog.normalize.output.multiplicative.OutputFieldMultiplicative: The default constructor.
OutputFieldMultiplicative(OutputFieldGroup, InputField) - Constructor for class org.encog.normalize.output.multiplicative.OutputFieldMultiplicative: Construct a multiplicative output field.
OutputFieldRangeMapped - Class in org.encog.normalize.output: A ranged mapped output field.
OutputFieldRangeMapped() - Constructor for class org.encog.normalize.output.OutputFieldRangeMapped: Default constructor, used mainly for reflection.
OutputFieldRangeMapped(InputField, double, double) - Constructor for class org.encog.normalize.output.OutputFieldRangeMapped: Construct a range mapped output field.
OutputFieldZAxis - Class in org.encog.normalize.output.zaxis: Both the multiplicative and z-axis normalization types allow a group of outputs to be adjusted so that the "vector length" is 1.
OutputFieldZAxis(OutputFieldGroup, InputField) - Constructor for class org.encog.normalize.output.zaxis.OutputFieldZAxis: Construct a ZAxis output field.
OutputFieldZAxisSynthetic - Class in org.encog.normalize.output.zaxis: This field represents the synthetic value used in Z-Axis normalization.
OutputFieldZAxisSynthetic(OutputFieldGroup) - Constructor for class org.encog.normalize.output.zaxis.OutputFieldZAxisSynthetic: Construct a synthetic output field for Z-Axis.
OutputOneOf - Class in org.encog.normalize.output.nominal: An output field that uses the "on of" technique to represent input data.
OutputOneOf() - Constructor for class org.encog.normalize.output.nominal.OutputOneOf: Default constructor for reflection.
OutputOneOf(double, double) - Constructor for class org.encog.normalize.output.nominal.OutputOneOf: Construct a one-of field and specify the true and false value.
OutputStreamPersistence - Class in org.encog.persist.location: This class allows Encog persistence to use a location that is based on an OutputStream.
OutputStreamPersistence(OutputStream) - Constructor for class org.encog.persist.location.OutputStreamPersistence: Construct the output stream location.

P

parse(String) - Method in class org.encog.util.csv.CSVFormat: Parse the specified string to a double.
parse(String) - Static method in class org.encog.util.http.FormUtility: Parse a URL query string.
parseAttributeName() - Method in class org.encog.parse.tags.read.ReadHTML: Parse the attribute name.
parseAttributeName() - Method in class org.encog.parse.tags.read.ReadTags: Parse an attribute name, if one is present.
parseDate(String) - Static method in class org.encog.bot.rss.RSS: Simple utility function that converts a RSS formatted date into a Java date.
parseDate(String) - Static method in class org.encog.util.csv.ReadCSV: Parse a date.
ParseError - Exception in org.encog.parse: Indicates an error has occured in one of the parsers.
ParseError(String) - Constructor for exception org.encog.parse.ParseError: Construct a message exception.
ParseError(Throwable) - Constructor for exception org.encog.parse.ParseError: Construct an exception that holds another exception.
parseString() - Method in class org.encog.parse.tags.read.ReadTags: Called to parse a double or single quote string.
parseTag() - Method in class org.encog.parse.tags.read.ReadTags: Called when a tag is detected.
passInit() - Method in class org.encog.normalize.segregate.index.IndexRangeSegregator: Nothing needs to be done to setup for a pass.
passInit() - Method in class org.encog.normalize.segregate.index.IndexSampleSegregator: Nothing needs to be done to setup for a pass.
passInit() - Method in class org.encog.normalize.segregate.IntegerBalanceSegregator: Init for a new pass.
passInit() - Method in class org.encog.normalize.segregate.RangeSegregator: Nothing needs to be done to setup for a pass.
passInit() - Method in interface org.encog.normalize.segregate.Segregator: Init for a pass.
PatternConst - Class in org.encog.neural.pattern: GUI constants for creating the patterns.
PatternError - Exception in org.encog.neural.pattern: This class is thrown when an error occurs while using one of the neural network pattern classes.
PatternError(String) - Constructor for exception org.encog.neural.pattern.PatternError: Construct a message exception.
PatternError(Throwable) - Constructor for exception org.encog.neural.pattern.PatternError: Construct an exception that holds another exception.
pause() - Method in class org.encog.neural.networks.training.propagation.Propagation: Pause the training to continue later.
pause() - Method in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation: Pause the training.
peek() - Method in class org.encog.parse.PeekableInputStream: Peek at the next character from the stream.
peek(int) - Method in class org.encog.parse.PeekableInputStream: Peek at a specified depth.
peek(String) - Method in class org.encog.parse.PeekableInputStream: Peek ahead and see if the specified string is present.
PeekableInputStream - Class in org.encog.parse: This is a special input stream that allows the program to peek one or more characters ahead in the file.
PeekableInputStream(InputStream) - Constructor for class org.encog.parse.PeekableInputStream: The constructor accepts an InputStream to setup the object.
performIteration(CalculateGradient, double[]) - Method in class org.encog.neural.networks.training.propagation.back.Backpropagation: Perform a training iteration.
performIteration(CalculateGradient, double[]) - Method in class org.encog.neural.networks.training.propagation.manhattan.ManhattanPropagation: Perform a training iteration.
performIteration(CalculateGradient, double[]) - Method in class org.encog.neural.networks.training.propagation.Propagation: Perform an iteration.
performIteration(CalculateGradient, double[]) - Method in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation: Perform a training iteration.
performIteration(CalculateGradient, double[]) - Method in class org.encog.neural.networks.training.propagation.scg.ScaledConjugateGradient: Not used.
performJobUnit(JobUnitContext) - Method in class org.encog.neural.prune.PruneIncremental: Perform an individual job unit, which is a single network to train and evaluate.
performJobUnit(JobUnitContext) - Method in class org.encog.util.concurrency.job.ConcurrentJob: Perform one job unit.
PersistenceLocation - Interface in org.encog.persist.location: A persistence location specifies how the persistence collection is stored.
PersistError - Exception in org.encog.persist: General error class for Encog persistence.
PersistError(String) - Constructor for exception org.encog.persist.PersistError: Construct a message exception.
PersistError(Throwable) - Constructor for exception org.encog.persist.PersistError: Construct an exception that holds another exception.
Persistor - Interface in org.encog.persist: This interface defines a class that can load and save an EncogPersistedObject.
PersistorUtil - Class in org.encog.persist.persistors: This class contains some utilities for persisting objects.
PersistReader - Class in org.encog.persist: Utility class for reading Encog persited object files.
PersistReader(PersistenceLocation) - Constructor for class org.encog.persist.PersistReader: Construct a persist reader.
PersistWriter - Class in org.encog.persist: Utility class for writing Encog persisted class files.
PersistWriter(PersistenceLocation) - Constructor for class org.encog.persist.PersistWriter: Create a writer for the specified location.
plural(TimeUnit) - Method in class org.encog.util.time.EnglishTimeUnitNames: Get the plural form for a TimeUnit.
plural(TimeUnit) - Method in interface org.encog.util.time.TimeUnitNames: Get the plural name for the specified time unit.
POSITIVE_ETA - Static variable in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation: The POSITIVE ETA value.
postIteration() - Method in class org.encog.neural.networks.training.BasicTraining: Call the strategies after an iteration.
postIteration() - Method in class org.encog.neural.networks.training.strategy.Greedy: Called just after a training iteration.
postIteration() - Method in class org.encog.neural.networks.training.strategy.HybridStrategy: Called just after a training iteration.
postIteration() - Method in interface org.encog.neural.networks.training.Strategy: Called just after a training iteration.
postIteration() - Method in class org.encog.neural.networks.training.strategy.ResetStrategy: Called just after a training iteration.
postIteration() - Method in class org.encog.neural.networks.training.strategy.SmartLearningRate: Called just after a training iteration.
postIteration() - Method in class org.encog.neural.networks.training.strategy.SmartMomentum: Called just after a training iteration.
postIteration() - Method in class org.encog.neural.networks.training.strategy.StopTrainingStrategy: Called just after a training iteration.
pow(double, double) - Static method in class org.encog.util.math.BoundMath: Calculate the power of a number.
preIteration() - Method in class org.encog.neural.networks.training.BasicTraining: Call the strategies before an iteration.
preIteration() - Method in class org.encog.neural.networks.training.strategy.Greedy: Called just before a training iteration.
preIteration() - Method in class org.encog.neural.networks.training.strategy.HybridStrategy: Called just before a training iteration.
preIteration() - Method in interface org.encog.neural.networks.training.Strategy: Called just before a training iteration.
preIteration() - Method in class org.encog.neural.networks.training.strategy.ResetStrategy: Called just before a training iteration.
preIteration() - Method in class org.encog.neural.networks.training.strategy.SmartLearningRate: Called just before a training iteration.
preIteration() - Method in class org.encog.neural.networks.training.strategy.SmartMomentum: Called just before a training iteration.
preIteration() - Method in class org.encog.neural.networks.training.strategy.StopTrainingStrategy: Called just before a training iteration.
preprocessLayer(Layer, NeuralData, Synapse) - Method in class org.encog.neural.networks.logic.FeedforwardLogic: Can be overridden by subclasses.
preprocessLayer(Layer, NeuralData, Synapse) - Method in class org.encog.neural.networks.logic.SimpleRecurrentLogic: Handle recurrent layers.
process(NeuralData) - Method in class org.encog.neural.networks.layers.BasicLayer: Process the input pattern.
process(NeuralData) - Method in class org.encog.neural.networks.layers.ContextLayer: Called to process input from the previous layer.
process(NeuralData) - Method in interface org.encog.neural.networks.layers.Layer: Process the data before it is modified by this layer.
process() - Method in class org.encog.neural.prune.PruneIncremental: Begin the prune process.
process() - Method in class org.encog.normalize.DataNormalization: Call this method to begin the normalization process.
process() - Method in class org.encog.util.benchmark.EncogBenchmark: Perform the benchmark.
process() - Method in class org.encog.util.concurrency.job.ConcurrentJob: Process the job.
processImage(Image) - Method in interface org.encog.util.downsample.Downsample: Process the specified image.
processImage(Image) - Method in class org.encog.util.downsample.RGBDownsample: Process the image and prepare it to be downsampled.
processTask(EncogTask) - Method in class org.encog.util.concurrency.EncogConcurrency: Process the specified task.
Propagation - Class in org.encog.neural.networks.training.propagation: Implements basic functionality that is needed by each of the propagation methods.
Propagation(BasicNetwork, NeuralDataSet) - Constructor for class org.encog.neural.networks.training.propagation.Propagation: Construct a propagation object.
PROPERTY_A1 - Static variable in class org.encog.neural.networks.logic.ARTLogic: Neural network property, the A1 parameter.
PROPERTY_ANNEAL_CYCLES - Static variable in class org.encog.neural.networks.logic.BoltzmannLogic: Neural network property, the number of annealing cycles to run.
PROPERTY_B1 - Static variable in class org.encog.neural.networks.logic.ARTLogic: Neural network property, the B1 parameter.
PROPERTY_C1 - Static variable in class org.encog.neural.networks.logic.ARTLogic: Neural network property, the C1 parameter.
PROPERTY_CENTER - Static variable in class org.encog.persist.persistors.RadialBasisFunctionLayerPersistor: The center of the RBF.
PROPERTY_CONTEXT - Static variable in class org.encog.persist.persistors.ContextLayerPersistor: Context tag.
PROPERTY_D1 - Static variable in class org.encog.neural.networks.logic.ARTLogic: Neural network property, the D1 parameter.
PROPERTY_L - Static variable in class org.encog.neural.networks.logic.ARTLogic: Neural network property, the L parameter.
PROPERTY_NEURONS - Static variable in class org.encog.persist.persistors.BasicLayerPersistor: The neurons property.
PROPERTY_PEAK - Static variable in class org.encog.persist.persistors.RadialBasisFunctionLayerPersistor: The peak of the RBF.
PROPERTY_RADIAL_FUNCTION - Static variable in class org.encog.persist.persistors.RadialBasisFunctionLayerPersistor: XML tag for the radial functions collection.
PROPERTY_RADIAL_FUNCTIONS - Static variable in class org.encog.persist.persistors.RadialBasisFunctionLayerPersistor: XML tag for the radial functions collection.
PROPERTY_RUN_CYCLES - Static variable in class org.encog.neural.networks.logic.BoltzmannLogic: Neural network property, the number of cycles to run.
PROPERTY_TEMPERATURE - Static variable in class org.encog.neural.networks.logic.BoltzmannLogic: Neural network property, the temperature.
PROPERTY_THRESHOLD - Static variable in class org.encog.persist.persistors.BasicLayerPersistor: The threshold property.
PROPERTY_VIGILANCE - Static variable in class org.encog.neural.networks.logic.ARTLogic: Neural network property, the vigilance parameter.
PROPERTY_WIDTH - Static variable in class org.encog.persist.persistors.RadialBasisFunctionLayerPersistor: The width of the RBF.
PROPERTY_X - Static variable in class org.encog.persist.persistors.BasicLayerPersistor: The x-coordinate to place this object at.
PROPERTY_Y - Static variable in class org.encog.persist.persistors.BasicLayerPersistor: The y-coordinate to place this object at.
PropertyData - Class in org.encog.neural.data: An Encog data object that can be used to hold property data.
PropertyData() - Constructor for class org.encog.neural.data.PropertyData
PropertyDataPersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the PropertyData class.
PropertyDataPersistor() - Constructor for class org.encog.persist.persistors.PropertyDataPersistor
prune(Layer, int) - Method in class org.encog.neural.prune.PruneSelective: Prune one of the neurons from this layer.
PruneIncremental - Class in org.encog.neural.prune: This class is used to help determine the optimal configuration for the hidden layers of a neural network.
PruneIncremental(NeuralDataSet, NeuralNetworkPattern, int, StatusReportable) - Constructor for class org.encog.neural.prune.PruneIncremental: Construct an object to determine the optimal number of hidden layers and neurons for the specified training data and pattern.
PruneSelective - Class in org.encog.neural.prune: Prune a neural network selectively.
PruneSelective(BasicNetwork) - Constructor for class org.encog.neural.prune.PruneSelective: Construct an object prune the neural network.
put(String, double[]) - Method in class org.encog.neural.networks.training.propagation.TrainingContinuation: Save a list of doubles.
putArray(double[]) - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing: Convert an array of doubles to the current best network.
putArray(Double[]) - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealingHelper: Used to pass the putArray call on to the parent object.
putArray(UNIT_TYPE[]) - Method in class org.encog.solve.anneal.SimulatedAnnealing: Store the array.

Q

QRDecomposition - Class in org.encog.matrix.decomposition: QR Decomposition.
QRDecomposition(Matrix) - Constructor for class org.encog.matrix.decomposition.QRDecomposition: QR Decomposition, computed by Householder reflections.

R

RadialBasisFunction - Interface in org.encog.util.math.rbf: Provides a generic interface to a radial basis function (RBF).
RadialBasisFunctionLayer - Class in org.encog.neural.networks.layers: This layer type makes use of several radial basis function to scale the output from this layer.
RadialBasisFunctionLayer() - Constructor for class org.encog.neural.networks.layers.RadialBasisFunctionLayer: Default constructor, mainly so the workbench can easily create a default layer.
RadialBasisFunctionLayer(int) - Constructor for class org.encog.neural.networks.layers.RadialBasisFunctionLayer: Construct a radial basis function layer.
RadialBasisFunctionLayerPersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the RadialBasisFunctionLayer class.
RadialBasisFunctionLayerPersistor() - Constructor for class org.encog.persist.persistors.RadialBasisFunctionLayerPersistor
RadialBasisFunctionMulti - Interface in org.encog.util.math.rbf: A multi-dimension RBF.
RadialBasisPattern - Class in org.encog.neural.pattern: A radial basis function (RBF) network uses several radial basis functions to provide a more dynamic hidden layer activation function than many other types of neural network.
RadialBasisPattern() - Constructor for class org.encog.neural.pattern.RadialBasisPattern
RANDOM_LENGTH - Static variable in class org.encog.util.http.FormUtility: The length of random string to create for multipart.
randomize() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing: Randomize the weights and thresholds.
randomize() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealingHelper: Call the owner's randomize method.
randomize() - Method in class org.encog.solve.anneal.SimulatedAnnealing: Randomize the weight matrix.
randomize(BasicNetwork) - Method in class org.encog.util.randomize.BasicRandomizer: Randomize the synapses and thresholds in the basic network based on an array, modify the array.
randomize(double[]) - Method in class org.encog.util.randomize.BasicRandomizer: Randomize the array based on an array, modify the array.
randomize(Double[]) - Method in class org.encog.util.randomize.BasicRandomizer: Randomize the array based on an array, modify the array.
randomize(double[][]) - Method in class org.encog.util.randomize.BasicRandomizer: Randomize the 2d array based on an array, modify the array.
randomize(Double[][]) - Method in class org.encog.util.randomize.BasicRandomizer: Randomize the 2d array based on an array, modify the array.
randomize(Matrix) - Method in class org.encog.util.randomize.BasicRandomizer: Randomize the matrix based on an array, modify the array.
randomize(double) - Method in class org.encog.util.randomize.ConsistentRandomizer: Generate a random number based on the range specified in the constructor.
randomize(double, double) - Static method in class org.encog.util.randomize.ConstRandomizer: Generate a random number in the specified range.
randomize(double) - Method in class org.encog.util.randomize.ConstRandomizer: Generate a random number based on the range specified in the constructor.
randomize(double) - Method in class org.encog.util.randomize.Distort: Distort the random number by the factor that was specified in the constructor.
randomize(double) - Method in class org.encog.util.randomize.FanInRandomizer: Starting with the specified number, randomize it to the degree specified by this randomizer.
randomize(double[]) - Method in class org.encog.util.randomize.FanInRandomizer: Randomize the array based on an array, modify the array.
randomize(Double[]) - Method in class org.encog.util.randomize.FanInRandomizer: Randomize the array based on an array, modify the array.
randomize(double[][]) - Method in class org.encog.util.randomize.FanInRandomizer: Randomize the 2d array based on an array, modify the array.
randomize(Double[][]) - Method in class org.encog.util.randomize.FanInRandomizer: Randomize the 2d array based on an array, modify the array.
randomize(Matrix) - Method in class org.encog.util.randomize.FanInRandomizer: Randomize the matrix based on an array, modify the array.
randomize(BasicNetwork) - Method in interface org.encog.util.randomize.Randomizer: Randomize the synapses and thresholds in the basic network based on an array, modify the array.
randomize(double) - Method in interface org.encog.util.randomize.Randomizer: Starting with the specified number, randomize it to the degree specified by this randomizer.
randomize(double[]) - Method in interface org.encog.util.randomize.Randomizer: Randomize the array based on an array, modify the array.
randomize(Double[]) - Method in interface org.encog.util.randomize.Randomizer: Randomize the array based on an array, modify the array.
randomize(double[][]) - Method in interface org.encog.util.randomize.Randomizer: Randomize the 2d array based on an array, modify the array.
randomize(Double[][]) - Method in interface org.encog.util.randomize.Randomizer: Randomize the 2d array based on an array, modify the array.
randomize(Matrix) - Method in interface org.encog.util.randomize.Randomizer: Randomize the matrix based on an array, modify the array.
randomize(double, double) - Static method in class org.encog.util.randomize.RangeRandomizer: Generate a random number in the specified range.
randomize(double) - Method in class org.encog.util.randomize.RangeRandomizer: Generate a random number based on the range specified in the constructor.
randomizeGaussianCentersAndWidths(double, double) - Method in class org.encog.neural.networks.layers.RadialBasisFunctionLayer: Set the gausian components to random values.
Randomizer - Interface in org.encog.util.randomize: Defines the interface for a class that is capable of randomizing the weights and thresholds of a neural network.
randomString() - Static method in class org.encog.util.http.FormUtility: Generate a random string, of a specified length.
RandomTrainingFactory - Class in org.encog.util.benchmark: Class used to generate random training sets.
range(double, double) - Method in class org.encog.util.math.LinearCongruentialGenerator: Generate a random number in the specified range.
RangeRandomizer - Class in org.encog.util.randomize: A randomizer that will create random weight and threshold values that are between a specified range.
RangeRandomizer(double, double) - Constructor for class org.encog.util.randomize.RangeRandomizer: Construct a range randomizer.
RangeSegregator - Class in org.encog.normalize.segregate: Range segregators are used to segregate data and include or exclude if it is within a certain range.
RangeSegregator() - Constructor for class org.encog.normalize.segregate.RangeSegregator: Default constructor for reflection.
RangeSegregator(InputField, boolean) - Constructor for class org.encog.normalize.segregate.RangeSegregator: Construct a range segregator.
rank() - Method in class org.encog.matrix.decomposition.SingularValueDecomposition: Effective numerical matrix rank
RBF_LAYER - Static variable in class org.encog.neural.pattern.RadialBasisPattern
read() - Method in class org.encog.parse.PeekableInputStream: Read a single byte from the stream.
read() - Method in class org.encog.parse.tags.read.ReadTags: Read a single character from the HTML source, if this function returns zero(0) then you should call getTag to see what tag was found.
ReadCSV - Class in org.encog.util.csv: Read and parse CSV format files.
ReadCSV(InputStream, boolean, char) - Constructor for class org.encog.util.csv.ReadCSV: Construct a CSV reader from an input stream.
ReadCSV(InputStream, boolean, CSVFormat) - Constructor for class org.encog.util.csv.ReadCSV: Construct a CSV reader from an input stream.
ReadCSV(String, boolean, char) - Constructor for class org.encog.util.csv.ReadCSV: Construct a CSV reader from a filename.
ReadCSV(String, boolean, CSVFormat) - Constructor for class org.encog.util.csv.ReadCSV: Construct a CSV reader from a filename.
readHeader() - Method in class org.encog.persist.PersistReader: Obtain the Encog header from the file.
ReadHTML - Class in org.encog.parse.tags.read: This class is designed to parse HTML documents.
ReadHTML(InputStream) - Constructor for class org.encog.parse.tags.read.ReadHTML: Construct a HTML reader.
readIntToTag() - Method in class org.encog.parse.tags.read.ReadXML: Read an integer that is contained between the current position, and the next tag.
readNextTag(String) - Method in class org.encog.persist.PersistReader: Read until the next tag of the specified name.
readNextText(String) - Method in class org.encog.persist.PersistReader: Read all text until the specified ending tag is found.
readObject(String) - Method in class org.encog.persist.PersistReader: Read the specific object, search through the objects until its found.
readPropertyBlock() - Method in class org.encog.parse.tags.read.ReadXML: Read all property data until an end tag, which corrisponds to the current tag, is found.
readStream(InputStream) - Static method in class org.encog.util.file.Directory: Read the entire contents of a stream into a string.
ReadTags - Class in org.encog.parse.tags.read: Base class used to read tags.
ReadTags(InputStream) - Constructor for class org.encog.parse.tags.read.ReadTags: The constructor should be passed an InputStream that we will parse from.
readTextFile(String) - Static method in class org.encog.util.file.Directory: Read the entire contents of a stream into a string.
readTextToTag() - Method in class org.encog.parse.tags.read.ReadXML: Read all text between the current position and the next tag.
readToTag() - Method in class org.encog.parse.tags.read.ReadTags: Read until we reach the next tag.
readValue(String) - Method in class org.encog.persist.PersistReader: Read the value in a period delimited string.
ReadXML - Class in org.encog.parse.tags.read: This class is designed to read XML.
ReadXML(InputStream) - Constructor for class org.encog.parse.tags.read.ReadXML: Construct an XML reader.
recur() - Method in class org.encog.neural.networks.layers.BasicLayer: Get the output from this layer when called in a recurrent manor.
recur() - Method in class org.encog.neural.networks.layers.ContextLayer: Called to get the output from this layer when called in a recurrent manor.
recur() - Method in interface org.encog.neural.networks.layers.Layer: Called on recurrent layers to provide recurrent output.
ReflectionUtil - Class in org.encog.util: This class includes some utilities to be used with reflection.
remove() - Method in class org.encog.neural.data.basic.BasicNeuralDataSet.BasicNeuralIterator: Removes are not supported.
remove() - Method in class org.encog.neural.data.buffer.BufferedNeuralDataSet.BufferedNeuralDataSetIterator: Not supported, will throw an error.
remove() - Method in class org.encog.neural.data.csv.CSVNeuralDataSet.CSVNeuralIterator: Removes are not supported.
remove(String) - Method in class org.encog.neural.data.PropertyData: Remove the specified property.
remove() - Method in class org.encog.neural.data.sql.SQLNeuralDataSet.SQLNeuralIterator: Removes are not supported.
remove() - Method in class org.encog.neural.data.union.UnionNeuralDataSet.UnionIterator: Not implemented.
remove() - Method in class org.encog.neural.data.xml.XMLNeuralDataSet.XMLNeuralIterator: Remove this iterator.
REMOVE_NOT_SUPPORTED - Static variable in class org.encog.neural.data.sql.SQLNeuralDataSet: Error message: removes are not supported.
renameTo(PersistenceLocation) - Method in class org.encog.persist.location.FilePersistence: Rename this file to a different location.
renameTo(PersistenceLocation) - Method in class org.encog.persist.location.InputStreamPersistence: Renames are not allowed on this type of location.
renameTo(PersistenceLocation) - Method in class org.encog.persist.location.OutputStreamPersistence: Renames are not allowed on this type of location.
renameTo(PersistenceLocation) - Method in interface org.encog.persist.location.PersistenceLocation: Attempt to rename this location.
renameTo(PersistenceLocation) - Method in class org.encog.persist.location.ResourcePersistence: Rename is not supported for resource persistence.
report(int, int, String) - Method in class org.encog.ConsoleStatusReportable: Simply display any status reports.
report(int, int, String) - Method in class org.encog.NullStatusReportable: Simply ignore any status reports.
report(int, int, String) - Method in interface org.encog.StatusReportable: Report on current status.
reportStatus(JobUnitContext, String) - Method in class org.encog.util.concurrency.job.ConcurrentJob: Report the status for this job.
requestNextTask() - Method in class org.encog.neural.prune.PruneIncremental: Request the next task.
requestNextTask() - Method in class org.encog.util.concurrency.job.ConcurrentJob: Request the next task to be processed.
RequireTwoPass - Interface in org.encog.normalize.output: Interface flag that indicates that a field type requires two passes.
reset() - Method in class org.encog.neural.networks.BasicNetwork: Reset the weight matrix and the thresholds.
reset() - Method in class org.encog.neural.networks.logic.ART1Logic: Reset the weight matrix back to starting values.
reset() - Method in interface org.encog.neural.networks.Network: Reset the weight matrix and the thresholds.
reset() - Method in class org.encog.neural.networks.training.competitive.BestMatchingUnit: Reset the "worst distance" back to a minimum value.
reset(double[]) - Method in class org.encog.neural.networks.training.propagation.gradient.GradientUtil: Reset for an iteration.
reset() - Method in class org.encog.util.ErrorCalculation: Reset the error accumulation to zero.
ResetStrategy - Class in org.encog.neural.networks.training.strategy: The reset strategy will reset the weights if the neural network fails to fall below a specified error by a specified number of cycles.
ResetStrategy(double, int) - Constructor for class org.encog.neural.networks.training.strategy.ResetStrategy: Construct a reset strategy.
ResilientPropagation - Class in org.encog.neural.networks.training.propagation.resilient: One problem with the backpropagation algorithm is that the magnitude of the partial derivative is usually too large or too small.
ResilientPropagation(BasicNetwork, NeuralDataSet) - Constructor for class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation: Construct a resilient training object.
ResilientPropagation(BasicNetwork, NeuralDataSet, double, double, double) - Constructor for class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation: Construct a resilient training object, allow the training parameters to be specified.
resolve() - Method in class org.encog.persist.persistors.generic.ObjectMapper: Resolve all references and place the correct objects.
resolveEncogClass(String) - Static method in class org.encog.util.ReflectionUtil: Resolve an encog class using its simple name.
ResourcePersistence - Class in org.encog.persist.location: A location that allows Encog objects to be read from a resource.
ResourcePersistence(String) - Constructor for class org.encog.persist.location.ResourcePersistence: Construct a location to read from the specified resource.
resume(TrainingContinuation) - Method in class org.encog.neural.networks.training.propagation.Propagation: Resume training.
resume(TrainingContinuation) - Method in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation: Resume training.
RGBDownsample - Class in org.encog.util.downsample: Downsample an image keeping the RGB colors.
RGBDownsample() - Constructor for class org.encog.util.downsample.RGBDownsample
rollIndex() - Method in class org.encog.normalize.segregate.index.IndexSegregator: Used to increase the current index as data is processed.
ROW - Static variable in class org.encog.persist.persistors.PersistorUtil: A matrix row.
rowInit() - Method in class org.encog.normalize.output.mapped.OutputFieldEncode: Not needed for this sort of output field.
rowInit() - Method in class org.encog.normalize.output.multiplicative.MultiplicativeGroup: Called to init this group for a new field.
rowInit() - Method in class org.encog.normalize.output.multiplicative.OutputFieldMultiplicative: Not needed for this sort of output field.
rowInit() - Method in class org.encog.normalize.output.nominal.OutputEquilateral: Determine which item's index is the value.
rowInit() - Method in class org.encog.normalize.output.nominal.OutputOneOf: Not needed for this sort of output field.
rowInit() - Method in interface org.encog.normalize.output.OutputField: Init this field for a new row.
rowInit() - Method in class org.encog.normalize.output.OutputFieldDirect: Not needed for this sort of output field.
rowInit() - Method in interface org.encog.normalize.output.OutputFieldGroup: Init the group for a new row.
rowInit() - Method in class org.encog.normalize.output.OutputFieldRangeMapped: Not needed for this sort of output field.
rowInit() - Method in class org.encog.normalize.output.zaxis.OutputFieldZAxis: Not needed for this sort of output field.
rowInit() - Method in class org.encog.normalize.output.zaxis.OutputFieldZAxisSynthetic: Not needed for this sort of output field.
rowInit() - Method in class org.encog.normalize.output.zaxis.ZAxisGroup: Initialize this group for a new row.
RSOMPattern - Class in org.encog.neural.pattern: A recurrent self organizing map is a self organizing map that has a recurrent context connection on the hidden layer.
RSOMPattern() - Constructor for class org.encog.neural.pattern.RSOMPattern
RSS - Class in org.encog.bot.rss: This is the class that actually parses the RSS and builds a collection of RSSItems.
RSS() - Constructor for class org.encog.bot.rss.RSS
RSSItem - Class in org.encog.bot.rss: This is the class that holds individual RSS items, or stories, for the RSS class.
RSSItem() - Constructor for class org.encog.bot.rss.RSSItem
run() - Method in class org.encog.neural.networks.logic.BoltzmannLogic: Run the network for all neurons present.
run() - Method in class org.encog.neural.networks.logic.HopfieldLogic: Perform one Hopfield iteration.
run() - Method in class org.encog.neural.networks.training.propagation.gradient.GradientWorker: The main loop for this thread.
run() - Method in class org.encog.solve.genetic.MateWorker: Mate the two chromosomes.
run() - Method in class org.encog.util.concurrency.job.JobUnitWorker: Run this job unit.
runUntilStable(int) - Method in class org.encog.neural.networks.logic.HopfieldLogic: Run the network until it becomes stable and does not change from more runs.

S

save(PersistenceLocation) - Method in class org.encog.persist.EncogMemoryCollection: Save the contents of this collection to a location.
save(EncogPersistedObject, WriteXML) - Method in interface org.encog.persist.Persistor: Save the specified object.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.ActivationBiPolarPersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.ActivationCompetitivePersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.ActivationGaussianPersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.ActivationLinearPersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.ActivationLOGPersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.ActivationSigmoidPersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.ActivationSINPersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.ActivationSoftMaxPersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.ActivationTANHPersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.BasicLayerPersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.BasicNetworkPersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.BasicNeuralDataSetPersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.ContextLayerPersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.DirectSynapsePersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.generic.GenericPersistor: Save the specified object.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.generic.Object2XML: Save the object to XML.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.OneToOneSynapsePersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.PropertyDataPersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.RadialBasisFunctionLayerPersistor: Save a RBF layer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.TextDataPersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.TrainingContinuationPersistor: Save the object.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.WeightedSynapsePersistor: Save the specified Encog object to an XML writer.
save(EncogPersistedObject, WriteXML) - Method in class org.encog.persist.persistors.WeightlessSynapsePersistor: Save the specified Encog object to an XML writer.
save(String, Serializable) - Static method in class org.encog.util.SerializeObject: Save the specified object.
saveCookies(URLConnection) - Method in class org.encog.util.http.CookieUtility: Once you have loaded cookies with loadCookies, you can call saveCookies to copy these cookies to a new HTTP request.
saveItems(WriteXML) - Method in class org.encog.persist.persistors.TrainingContinuationPersistor: Save items.
saveMatrix(Matrix, WriteXML) - Static method in class org.encog.persist.persistors.PersistorUtil: Save the specified matrix.
saveModified(WriteXML, String, String, String) - Method in class org.encog.persist.PersistReader: Modify the properties of this object.
saveTo(WriteXML, String) - Method in class org.encog.persist.PersistReader: Save all objects to the specified steam, skip the one specified by the skip parameter.
ScaledConjugateGradient - Class in org.encog.neural.networks.training.propagation.scg: This is a training class that makes use of scaled conjugate gradient methods.
ScaledConjugateGradient(BasicNetwork, NeuralDataSet) - Constructor for class org.encog.neural.networks.training.propagation.scg.ScaledConjugateGradient: Construct a training class.
scan(File) - Method in class org.encog.util.GenerateClasslist: Scan the specified directory.
search(String) - Method in class org.encog.util.YahooSearch: Called to extract a list from the specified URL.
SECONDS_INA_DAY - Static variable in class org.encog.util.Format: Seconds in a day.
SECONDS_INA_HOUR - Static variable in class org.encog.util.Format: Seconds in an hour.
SECONDS_INA_MINUTE - Static variable in class org.encog.util.Format: Seconds in a minute.
SECONDS_MINUTE - Static variable in class org.encog.util.time.TimeSpan: Seconds in a minute.
SegregationRange - Class in org.encog.normalize.segregate: Specifies a range that might be included or excluded.
SegregationRange() - Constructor for class org.encog.normalize.segregate.SegregationRange: Default constructor for reflection.
SegregationRange(double, double, boolean) - Constructor for class org.encog.normalize.segregate.SegregationRange: Construct a segregation range.
Segregator - Interface in org.encog.normalize.segregate: Segregators are used to exclude certain rows.
SerializeObject - Class in org.encog.util: Load or save an object using Java serialization.
set(double) - Method in class org.encog.matrix.Matrix: Set every value in the matrix to the specified value.
set(int, int, double) - Method in class org.encog.matrix.Matrix: Set an individual cell in the matrix to the specified value.
set(Matrix) - Method in class org.encog.matrix.Matrix: Set this matrix's values to that of another matrix.
set(String, String) - Method in class org.encog.neural.data.PropertyData: Set the specified property.
set(String, Object) - Method in class org.encog.neural.networks.training.propagation.TrainingContinuation: Set a value to a string.
setA1(double) - Method in class org.encog.neural.networks.logic.ART1Logic: Set the A1 parameter.
setA1(double) - Method in class org.encog.neural.pattern.ART1Pattern: Set the A1 parameter.
setAction(Address) - Method in class org.encog.bot.browse.range.Form: Set the action for the form.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.networks.layers.BasicLayer: Set the activation function for this layer.
setActivationFunction(ActivationFunction) - Method in interface org.encog.neural.networks.layers.Layer: Set a new activation function for this layer.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.ADALINEPattern: Not used, the BAM uses a bipoloar activation function.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.ART1Pattern: This method will throw an error, you can't set the activation function for an ART1.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.BAMPattern: Not used, the BAM uses a bipoloar activation function.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.BoltzmannPattern: Not used, will throw an exception.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.CPNPattern: This method will throw an error.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.ElmanPattern: Set the activation function to use on each of the layers.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.FeedForwardPattern: Set the activation function to use on each of the layers.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.HopfieldPattern: Set the activation function to use.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.JordanPattern: Set the activation function to use on each of the layers.
setActivationFunction(ActivationFunction) - Method in interface org.encog.neural.pattern.NeuralNetworkPattern: Set the activation function to be used for all created layers that allow an activation function to be specified.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.RadialBasisPattern: Set the activation function, this is an error.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.RSOMPattern: Set the activation function.
setActivationFunction(ActivationFunction) - Method in class org.encog.neural.pattern.SOMPattern: Set the activation function.
setAnnealCycles(int) - Method in class org.encog.neural.pattern.BoltzmannPattern: Set the number of annealing cycles per run.
setAttribute(String, String) - Method in class org.encog.parse.tags.Tag: Set a HTML attribute.
setAutoDecay(int, double, double, double, double) - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining: Setup autodecay.
setB1(double) - Method in class org.encog.neural.networks.logic.ART1Logic: Set the B1 parameter.
setB1(double) - Method in class org.encog.neural.pattern.ART1Pattern: Set the B1 parameter.
setBegin(int) - Method in class org.encog.bot.browse.range.DocumentRange: Set the beginning index.
setC1(double) - Method in class org.encog.neural.networks.logic.ART1Logic: Set the C1 parameter.
setC1(double) - Method in class org.encog.neural.pattern.ART1Pattern: Set the C1 parameter.
setCatchAll(double) - Method in class org.encog.normalize.output.mapped.OutputFieldEncode: Set the catch all value.
setChromosome(int, Chromosome<GENE_TYPE>) - Method in class org.encog.solve.genetic.GeneticAlgorithm: Set the specified chromosome.
setChromosomes(Chromosome<GENE_TYPE>[]) - Method in class org.encog.solve.genetic.GeneticAlgorithm: Set the entire population.
setClassAttribute(String) - Method in class org.encog.bot.browse.range.DocumentRange
setCloseConnection(boolean) - Method in class org.encog.neural.data.sql.SQLNeuralDataSet: Allows you to determine if the connection should be closed.
setCode(String) - Method in class org.encog.bot.dataunit.CodeDataUnit: Set the code to the specified string.
setConsoleLevel(Level) - Static method in class org.encog.util.logging.Logging: Set the logging level for console.
setCSVFormat(CSVFormat) - Method in class org.encog.normalize.DataNormalization: Set the CSV format to use.
setCurrentBlue(int) - Method in class org.encog.util.downsample.RGBDownsample: Set the current blue average.
setCurrentGreen(int) - Method in class org.encog.util.downsample.RGBDownsample: Set the current green average.
setCurrentPage(WebPage) - Method in class org.encog.bot.browse.Browser: Set the current page.
setCurrentRed(int) - Method in class org.encog.util.downsample.RGBDownsample: Set the current red average.
setCurrentState(BiPolarNeuralData) - Method in class org.encog.neural.networks.logic.ThermalLogic
setCurrentValue(double) - Method in class org.encog.normalize.input.BasicInputField: Set the current value of this field.
setCurrentValue(double) - Method in interface org.encog.normalize.input.InputField: Set the current value of this field.
setCutLength(int) - Method in class org.encog.solve.genetic.GeneticAlgorithm: Set the cut length.
setCycles(int) - Method in class org.encog.solve.anneal.SimulatedAnnealing
setD1(double) - Method in class org.encog.neural.networks.logic.ART1Logic: Set the D1 parameter.
setD1(double) - Method in class org.encog.neural.pattern.ART1Pattern: Set the D1 parameter.
setData(double[]) - Method in class org.encog.neural.data.basic.BasicNeuralData: Set the entire data array.
setData(int, double) - Method in class org.encog.neural.data.basic.BasicNeuralData: Set the data element specified by the index.
setData(List<NeuralDataPair>) - Method in class org.encog.neural.data.basic.BasicNeuralDataSet
setData(double[]) - Method in class org.encog.neural.data.bipolar.BiPolarNeuralData: Store the array.
setData(int, boolean) - Method in class org.encog.neural.data.bipolar.BiPolarNeuralData: Set the specified index of this object as a boolean.
setData(int, double) - Method in class org.encog.neural.data.bipolar.BiPolarNeuralData: Set the specified index of this object as a double.
setData(MarketDataType, double) - Method in class org.encog.neural.data.market.loader.LoadedMarketData: Set financial data for this date.
setData(double[]) - Method in interface org.encog.neural.data.NeuralData: Set all of the data as an array of doubles.
setData(int, double) - Method in interface org.encog.neural.data.NeuralData: Set the specified element.
setData(double[]) - Method in class org.encog.neural.data.temporal.TemporalPoint
setData(int, double) - Method in class org.encog.neural.data.temporal.TemporalPoint: Set the data at the specified index.
setDate(Date) - Method in class org.encog.bot.rss.RSSItem: Set the publication date.
setDescription(String) - Method in class org.encog.bot.rss.RSSItem: Get the description.
setDescription(String) - Method in class org.encog.matrix.Matrix: Set the description for this object.
setDescription(String) - Method in class org.encog.neural.activation.BasicActivationFunction: Ignore the description, it is not used for activation functions.
setDescription(String) - Method in class org.encog.neural.data.basic.BasicNeuralDataSet
setDescription(String) - Method in class org.encog.neural.data.PropertyData: Set the description for this object.
setDescription(String) - Method in class org.encog.neural.data.TextData: Set the description of this object.
setDescription(String) - Method in class org.encog.neural.networks.BasicNetwork: Set the description for this object.
setDescription(String) - Method in class org.encog.neural.networks.layers.BasicLayer
setDescription(String) - Method in interface org.encog.neural.networks.Network: Set the description for this object.
setDescription(String) - Method in class org.encog.neural.networks.synapse.BasicSynapse: The EncogPersistedObject requires a name and description, however, these are not used on synapses.
setDescription(String) - Method in class org.encog.neural.networks.training.propagation.TrainingContinuation: Set the description.
setDescription(String) - Method in class org.encog.normalize.DataNormalization: Set the current description.
setDescription(String) - Method in interface org.encog.persist.EncogPersistedObject: Set the description of this object.
setDesiredSetSize(int) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
setEnd(int) - Method in class org.encog.bot.browse.range.DocumentRange: Set the ending index.
setError(double) - Method in class org.encog.neural.networks.training.BasicTraining
setError(double) - Method in interface org.encog.neural.networks.training.Train
setError(double) - Method in class org.encog.util.simple.TrainingDialog: Set the current error.
setF1Neurons(int) - Method in class org.encog.neural.pattern.BAMPattern: Set the F1 neurons.
setF2Neurons(int) - Method in class org.encog.neural.pattern.BAMPattern: Set the output neurons.
setForceWinner(boolean) - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining: Determine if a winner is to be forced.
setFrom(NeuralData) - Method in class org.encog.neural.networks.NeuralDataMapping: Set the from data.
setFromLayer(Layer) - Method in class org.encog.neural.networks.synapse.BasicSynapse: Set the from layer for this synapse.
setFromLayer(Layer) - Method in interface org.encog.neural.networks.synapse.Synapse: Set the from layer for this synapse.
setGene(int, GENE_TYPE) - Method in class org.encog.solve.genetic.Chromosome: Set the specified gene's value.
setGenes(Double[]) - Method in class org.encog.neural.networks.training.genetic.NeuralChromosome: Set all genes.
setGenes(GENE_TYPE[]) - Method in class org.encog.solve.genetic.Chromosome: Set the entire gene array.
setGenesDirect(GENE_TYPE[]) - Method in class org.encog.solve.genetic.Chromosome: Set the genes directly, not allowed to be overridden.
setGenetic(NeuralGeneticAlgorithm.NeuralGeneticAlgorithmHelper) - Method in class org.encog.neural.networks.training.genetic.NeuralGeneticAlgorithm: Set the genetic helper class.
setGeneticAlgorithm(GeneticAlgorithm<GENE_TYPE>) - Method in class org.encog.solve.genetic.Chromosome: Set the genetic algorithm.
setHighSequence(int) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
setID(int) - Method in class org.encog.neural.networks.layers.BasicLayer: Set the id for this layer.
setID(int) - Method in interface org.encog.neural.networks.layers.Layer: Set the id for this layer.
setIdAttribute(String) - Method in class org.encog.bot.browse.range.DocumentRange
setIdeal(boolean) - Method in class org.encog.normalize.output.BasicOutputField: Set if this is an ideal field.
setIdeal(boolean) - Method in interface org.encog.normalize.output.OutputField: Set whether this field is part of the ideal output for a network.
setImage(Image) - Method in class org.encog.neural.data.image.ImageNeuralData
setIndex(int) - Method in class org.encog.neural.data.temporal.TemporalDataDescription
setInputNeurons(int) - Method in class org.encog.neural.pattern.ADALINEPattern: Set the input neurons.
setInputNeurons(int) - Method in class org.encog.neural.pattern.ART1Pattern: Set the input neuron (F1 layer) count.
setInputNeurons(int) - Method in class org.encog.neural.pattern.BAMPattern: Set the number of input neurons.
setInputNeurons(int) - Method in class org.encog.neural.pattern.BoltzmannPattern: Set the number of input neurons.
setInputNeurons(int) - Method in class org.encog.neural.pattern.CPNPattern: Set the number of input neurons.
setInputNeurons(int) - Method in class org.encog.neural.pattern.ElmanPattern: Set the number of input neurons.
setInputNeurons(int) - Method in class org.encog.neural.pattern.FeedForwardPattern: Set the number of input neurons.
setInputNeurons(int) - Method in class org.encog.neural.pattern.HopfieldPattern: Set the number of input neurons, this must match the output neurons.
setInputNeurons(int) - Method in class org.encog.neural.pattern.JordanPattern: Set the number of input neurons.
setInputNeurons(int) - Method in interface org.encog.neural.pattern.NeuralNetworkPattern: Set the number of input neurons.
setInputNeurons(int) - Method in class org.encog.neural.pattern.RadialBasisPattern: Set the number of input neurons.
setInputNeurons(int) - Method in class org.encog.neural.pattern.RSOMPattern: Set the input neuron count.
setInputNeurons(int) - Method in class org.encog.neural.pattern.SOMPattern: Set the input neuron count.
setInputWindowSize(int) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
setInstarCount(int) - Method in class org.encog.neural.pattern.CPNPattern: Set the number of neurons in the instar layer.
setIterations(int) - Method in class org.encog.util.simple.TrainingDialog: Set the number of iterations.
setJobUnit(Object) - Method in class org.encog.util.concurrency.job.JobUnitContext: Set the job unit.
setL(double) - Method in class org.encog.neural.networks.logic.ART1Logic: Set the L parameter.
setL(double) - Method in class org.encog.neural.pattern.ART1Pattern: Set the L parameter.
setLearningRate(double) - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining: Set the learning rate.
setLearningRate(double) - Method in class org.encog.neural.networks.training.cpn.TrainInstar: Set the learning rate.
setLearningRate(double) - Method in class org.encog.neural.networks.training.cpn.TrainOutstar: Set the learning rate.
setLearningRate(double) - Method in interface org.encog.neural.networks.training.LearningRate: Set the learning rate.
setLearningRate(double) - Method in class org.encog.neural.networks.training.propagation.back.Backpropagation: Set the learning rate, this is value is essentially a percent.
setLearningRate(double) - Method in class org.encog.neural.networks.training.propagation.manhattan.ManhattanPropagation: Set the learning rate.
setLearningRate(double) - Method in class org.encog.neural.networks.training.simple.TrainAdaline: Set the learning rate.
setLink(String) - Method in class org.encog.bot.rss.RSSItem: Set the hyperlink.
setLogic(NeuralLogic) - Method in class org.encog.neural.networks.BasicNetwork: Set the type of logic this network should use.
setLowSequence(int) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
setMatingPopulation(double) - Method in class org.encog.solve.genetic.GeneticAlgorithm: Set the mating population percent.
setMatrix(int, int, int, int, Matrix) - Method in class org.encog.matrix.Matrix: Set a submatrix.
setMatrix(int[], int[], Matrix) - Method in class org.encog.matrix.Matrix: Set a submatrix.
setMatrix(int[], int, int, Matrix) - Method in class org.encog.matrix.Matrix: Set a submatrix.
setMatrix(int, int, int[], Matrix) - Method in class org.encog.matrix.Matrix: Set a submatrix.
setMatrix(Matrix) - Method in class org.encog.neural.networks.synapse.DirectSynapse: Attempt to set the matrix for this layer.
setMatrix(Matrix) - Method in class org.encog.neural.networks.synapse.OneToOneSynapse: Attempt to set the matrix for this layer.
setMatrix(Matrix) - Method in interface org.encog.neural.networks.synapse.Synapse: Assign a new weight and threshold matrix to this layer.
setMatrix(Matrix) - Method in class org.encog.neural.networks.synapse.WeightedSynapse: Assign a new weight and threshold matrix to this layer.
setMatrix(Matrix) - Method in class org.encog.neural.networks.synapse.WeightlessSynapse: Attempt to set the matrix for this layer.
setMax(double) - Method in class org.encog.normalize.input.BasicInputField: Set the current max value.
setMax(double) - Method in interface org.encog.normalize.input.InputField: Set the current max value.
setMaxThreads(int) - Method in class org.encog.util.concurrency.EncogConcurrency: Set the maximum number of threads to use.
setMaxThreadsToCoreCount() - Method in class org.encog.util.concurrency.EncogConcurrency: Set the max threads to the number of processors.
setMethod(Form.Method) - Method in class org.encog.bot.browse.range.Form: Set the method to send the form.
setMin(double) - Method in class org.encog.normalize.input.BasicInputField: Set the current min value.
setMin(double) - Method in interface org.encog.normalize.input.InputField: Set the current min value.
setMomentum(double) - Method in interface org.encog.neural.networks.training.Momentum: Set the momentum.
setMomentum(double) - Method in class org.encog.neural.networks.training.propagation.back.Backpropagation: Set the momentum for training.
setMutationPercent(double) - Method in class org.encog.solve.genetic.GeneticAlgorithm: Set the mutation percent.
setName(String) - Method in class org.encog.bot.browse.range.FormElement: Set the name of this form element.
setName(String) - Method in class org.encog.matrix.Matrix
setName(String) - Method in class org.encog.neural.activation.BasicActivationFunction: Ignore the name, it is not used for activation functions.
setName(String) - Method in class org.encog.neural.data.basic.BasicNeuralDataSet
setName(String) - Method in class org.encog.neural.data.PropertyData: Set the name of this property.
setName(String) - Method in class org.encog.neural.data.TextData: Set the name of this object.
setName(String) - Method in class org.encog.neural.networks.BasicNetwork
setName(String) - Method in class org.encog.neural.networks.layers.BasicLayer
setName(String) - Method in interface org.encog.neural.networks.Network
setName(String) - Method in class org.encog.neural.networks.synapse.BasicSynapse: The EncogPersistedObject requires a name and description, however, these are not used on synapses.
setName(String) - Method in class org.encog.neural.networks.training.propagation.TrainingContinuation: Set the name of this object.
setName(String) - Method in class org.encog.normalize.DataNormalization: Set the name of this object.
setName(String) - Method in class org.encog.parse.tags.Tag: Set the tag name.
setName(String) - Method in interface org.encog.persist.EncogPersistedObject: Set the name of this object.
setNetwork(BasicNetwork) - Method in class org.encog.neural.networks.layers.BasicLayer: Set the network for this layer.
setNetwork(BasicNetwork) - Method in interface org.encog.neural.networks.layers.Layer: Set the network that this layer belongs to.
setNetwork(BasicNetwork) - Method in class org.encog.neural.networks.training.genetic.NeuralChromosome
setNeuronCount(int) - Method in class org.encog.neural.networks.layers.BasicLayer: Set the neuron count.
setNeuronCount(int) - Method in interface org.encog.neural.networks.layers.Layer: Set the neuron count, this will NOT adjust the synapses, or thresholds other code must do that.
setNumThreads(int) - Method in class org.encog.neural.networks.training.propagation.Propagation: Set the number of threads.
setOutput(NeuralData) - Method in class org.encog.neural.networks.NeuralOutputHolder: Set the output.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.ADALINEPattern: Set the output neurons.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.ART1Pattern: Set the output neuron (F2 layer) count.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.BAMPattern: Set the number of output neurons.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.BoltzmannPattern: Set the number of output neurons.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.CPNPattern: Set the number of output neurons.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.ElmanPattern: Set the number of output neurons.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.FeedForwardPattern: Set the number of output neurons.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.HopfieldPattern: Set the number of output neurons, should not be used with a hopfield neural network, because the number of input neurons defines the number of output neurons.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.JordanPattern: Set the number of output neurons.
setOutputNeurons(int) - Method in interface org.encog.neural.pattern.NeuralNetworkPattern: Set the number of output neurons.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.RadialBasisPattern: Set the number of output neurons.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.RSOMPattern: Set the output neuron count.
setOutputNeurons(int) - Method in class org.encog.neural.pattern.SOMPattern: Set the output neuron count.
setOutstarCount(int) - Method in class org.encog.neural.pattern.CPNPattern: Set the number of neurons in the outstar level, this level is mapped to the "output" level.
setOwner(Form) - Method in class org.encog.bot.browse.range.FormElement: Set the owner of this form element.
setOwner(ConcurrentJob) - Method in class org.encog.util.concurrency.job.JobUnitContext: Set the job owner.
setPair(NeuralDataPair) - Method in class org.encog.normalize.input.NeuralDataFieldHolder: Set the pair.
setParams(double, double) - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining: Set the learning rate and radius.
setParent(DocumentRange) - Method in class org.encog.bot.browse.range.DocumentRange: Set the parent.
setPercentToMate(double) - Method in class org.encog.solve.genetic.GeneticAlgorithm: Set the percent to mate.
setPixelMap(int[]) - Method in class org.encog.util.downsample.RGBDownsample: Set the pixel map.
setPopulationSize(int) - Method in class org.encog.solve.genetic.GeneticAlgorithm: Set the population size.
setPredictWindowSize(int) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
setPreventRepeat(boolean) - Method in class org.encog.solve.genetic.GeneticAlgorithm: Set the gene.
setProperty(String, double) - Method in class org.encog.neural.networks.BasicNetwork: Set a property as a double.
setProperty(String, long) - Method in class org.encog.neural.networks.BasicNetwork: Set a property as a long.
setProperty(String, String) - Method in class org.encog.neural.networks.BasicNetwork: Set a property as a double.
setRadialBasisFunction(RadialBasisFunction[]) - Method in class org.encog.neural.networks.layers.RadialBasisFunctionLayer: Set the RBF array used by this layer.
setRadius(double) - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodBubble: Set the radius.
setRadius(double) - Method in interface org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodFunction: Set the radius.
setRadius(double) - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodGaussian: Set the radius.
setRadius(double) - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodGaussianMulti: Set the radius.
setRadius(double) - Method in class org.encog.neural.networks.training.competitive.neighborhood.NeighborhoodSingle: Set the radius.
setReport(StatusReportable) - Method in class org.encog.normalize.DataNormalization: Set the object that this one is reporting to.
setRunCycles(int) - Method in class org.encog.neural.pattern.BoltzmannPattern: Set the number of cycles per run.
setScore(double) - Method in class org.encog.solve.anneal.SimulatedAnnealing: Set the score.
setScore(double) - Method in class org.encog.solve.genetic.Chromosome: Set the score for this chromosome.
setSeed(long) - Method in class org.encog.util.math.LinearCongruentialGenerator: Set the seed value.
setSequence(int) - Method in class org.encog.neural.data.temporal.TemporalPoint
setSequenceGrandularity(TimeUnit) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
setShouldMinimize(boolean) - Method in class org.encog.solve.anneal.SimulatedAnnealing: Should the score be minimized.
setShouldMinimize(boolean) - Method in class org.encog.solve.genetic.GeneticAlgorithm: Determine if the score should be minimized.
setSource(WebPage) - Method in class org.encog.bot.browse.range.DocumentRange: Set the source web page.
setStartingPoint(Date) - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet
setStartTemperature(double) - Method in class org.encog.solve.anneal.SimulatedAnnealing
setStopTemperature(double) - Method in class org.encog.solve.anneal.SimulatedAnnealing
setTag(Tag) - Method in class org.encog.bot.dataunit.TagDataUnit: Set the tag that this data unit is based on.
setTarget(Address) - Method in class org.encog.bot.browse.range.Link: Set the target of this link.
setTarget(NormalizationStorage) - Method in class org.encog.normalize.DataNormalization: Determines where the normalized data will be sent.
setTaskNumber(int) - Method in class org.encog.util.concurrency.job.JobUnitContext: Set the task number.
setTemperature(double) - Method in class org.encog.neural.networks.logic.BoltzmannLogic: Set the network temperature.
setTemperature(double) - Method in class org.encog.neural.pattern.BoltzmannPattern: Set the temperature.
setTemperature(double) - Method in class org.encog.solve.anneal.SimulatedAnnealing
setText(String) - Method in class org.encog.bot.dataunit.TextDataUnit: Set the text for this data unit.
setText(String) - Method in class org.encog.neural.data.TextData: Set the text held by this object.
setThreshold(double[]) - Method in class org.encog.neural.networks.layers.BasicLayer: Set the threshold array.
setThreshold(int, double) - Method in class org.encog.neural.networks.layers.BasicLayer: Set the specified threshold value.
setThreshold(double[]) - Method in interface org.encog.neural.networks.layers.Layer: Set the threshold array for this layer.
setThreshold(int, double) - Method in interface org.encog.neural.networks.layers.Layer: Set an individual threshold value.
setTime(int) - Method in class org.encog.util.simple.TrainingDialog: Set the time.
setTitle(DocumentRange) - Method in class org.encog.bot.browse.WebPage: Set the title of this document.
setTitle(String) - Method in class org.encog.bot.rss.RSSItem: Set the item title.
setTo(NeuralData) - Method in class org.encog.neural.networks.NeuralDataMapping: Set the target data.
setToLayer(Layer) - Method in class org.encog.neural.networks.synapse.BasicSynapse: Set the target layer from this synapse.
setToLayer(Layer) - Method in interface org.encog.neural.networks.synapse.Synapse: Set the target layer from this synapse.
setTraining(NeuralDataSet) - Method in class org.encog.neural.networks.training.BasicTraining: Set the training object that this strategy is working with.
setType(String) - Method in class org.encog.bot.browse.range.Input: Set the type of this input element.
setType(Tag.Type) - Method in class org.encog.parse.tags.Tag: Set the tag type.
setUsedForNetworkInput(boolean) - Method in class org.encog.normalize.input.BasicInputField: This is needed so that the buildForNetworkInput method of the normalization class knows how many input fields to expect.
setValue(String) - Method in class org.encog.bot.browse.range.FormElement: Set the value for this form element.
setVigilance(double) - Method in class org.encog.neural.networks.logic.ART1Logic: Set the vigilance.
setVigilance(double) - Method in class org.encog.neural.pattern.ART1Pattern: Set the vigilance for the network.
setWidth(double) - Method in class org.encog.util.math.rbf.GaussianFunction
setWidth(double) - Method in class org.encog.util.math.rbf.GaussianFunctionMulti: Set the width for all dimensions.
setWidth(double) - Method in interface org.encog.util.math.rbf.RadialBasisFunction: Set the width.
setWidth(double) - Method in interface org.encog.util.math.rbf.RadialBasisFunctionMulti: Set the width.
setX(int) - Method in class org.encog.neural.networks.layers.BasicLayer: Set the x coordinate for this layer.
setX(int) - Method in interface org.encog.neural.networks.layers.Layer: Set the x coordinate.
setY(int) - Method in class org.encog.neural.networks.layers.BasicLayer: Set the y coordinate for this layer.
setY(int) - Method in interface org.encog.neural.networks.layers.Layer: Set the y coordinate.
shouldAccessField(Field, boolean) - Static method in class org.encog.util.ReflectionUtil: Determine if Encog persistence should access the specified field.
shouldInclude() - Method in class org.encog.normalize.segregate.index.IndexRangeSegregator: Determines if the current row should be included.
shouldInclude() - Method in class org.encog.normalize.segregate.index.IndexSampleSegregator: Should this row be included.
shouldInclude() - Method in class org.encog.normalize.segregate.IntegerBalanceSegregator: Determine of the current row should be included.
shouldInclude() - Method in class org.encog.normalize.segregate.RangeSegregator
shouldInclude() - Method in interface org.encog.normalize.segregate.Segregator: Should this row be included, according to this segregator.
shouldMinimize() - Method in interface org.encog.neural.networks.training.CalculateScore
shouldMinimize() - Method in class org.encog.neural.networks.training.TrainingSetScore: A training set based score should always seek to lower the error, as a result, this method always returns true.
shouldStop() - Method in class org.encog.neural.networks.training.strategy.StopTrainingStrategy
shouldStop() - Method in class org.encog.util.simple.TrainingDialog
shutdown(long) - Method in class org.encog.util.concurrency.EncogConcurrency: Wait for all threads in the pool to complete.
simpleFeedForward(int, int, int, int, boolean) - Static method in class org.encog.util.simple.EncogUtility: Create a simple feedforward neural network.
SimpleIntensityDownsample - Class in org.encog.util.downsample: Downsample an image using a simple intensity scale.
SimpleIntensityDownsample() - Constructor for class org.encog.util.downsample.SimpleIntensityDownsample
SimpleRecurrentLogic - Class in org.encog.neural.networks.logic: Provides the neural logic for an Simple Recurrent Network (SRN) type network.
SimpleRecurrentLogic() - Constructor for class org.encog.neural.networks.logic.SimpleRecurrentLogic
SimulatedAnnealing<UNIT_TYPE> - Class in org.encog.solve.anneal: Simulated annealing is a common training method.
SimulatedAnnealing() - Constructor for class org.encog.solve.anneal.SimulatedAnnealing
sin(double) - Static method in class org.encog.util.math.BoundMath: Calculate the sin.
singular(TimeUnit) - Method in class org.encog.util.time.EnglishTimeUnitNames: Get the singular form for a TimeUnit.
singular(TimeUnit) - Method in interface org.encog.util.time.TimeUnitNames: Get the singular form of the specified time unit.
SingularValueDecomposition - Class in org.encog.matrix.decomposition: Singular Value Decomposition.
SingularValueDecomposition(Matrix) - Constructor for class org.encog.matrix.decomposition.SingularValueDecomposition: Construct the singular value decomposition
size() - Method in class org.encog.matrix.Matrix: Get the size of the array.
size() - Method in class org.encog.neural.data.basic.BasicNeuralData: Get the number of data elements present.
size() - Method in class org.encog.neural.data.bipolar.BiPolarNeuralData: Get the size of this data object.
size() - Method in interface org.encog.neural.data.NeuralData
size() - Method in class org.encog.neural.data.PropertyData
skip(long) - Method in class org.encog.parse.PeekableInputStream: Skip the specified number of bytes.
SmartLearningRate - Class in org.encog.neural.networks.training.strategy: Attempt to automatically set the learning rate in a learning method that supports a learning rate.
SmartLearningRate() - Constructor for class org.encog.neural.networks.training.strategy.SmartLearningRate
SmartMomentum - Class in org.encog.neural.networks.training.strategy: Attempt to automatically set a momentum in a training algorithm that supports momentum.
SmartMomentum() - Constructor for class org.encog.neural.networks.training.strategy.SmartMomentum
solve(Matrix) - Method in class org.encog.matrix.decomposition.CholeskyDecomposition: Solve A*X = B.
solve(Matrix) - Method in class org.encog.matrix.decomposition.LUDecomposition: Solve A*X = B
solve(Matrix) - Method in class org.encog.matrix.decomposition.QRDecomposition: Least squares solution of A*X = B
solve(Matrix) - Method in class org.encog.matrix.Matrix: Solve A*X = B.
SOMLogic - Class in org.encog.neural.networks.logic: Not really any different than the simple recurrent logic, but leaves for Encog SOM logic to be expanded in the future, and allows SOM specific trainers to exclude this logic type.
SOMLogic() - Constructor for class org.encog.neural.networks.logic.SOMLogic
SOMPattern - Class in org.encog.neural.pattern: A self organizing map is a neural network pattern with an input and output layer.
SOMPattern() - Constructor for class org.encog.neural.pattern.SOMPattern
sort() - Method in class org.encog.neural.networks.structure.NeuralStructure: Sort the layers and synapses.
sortChromosomes() - Method in class org.encog.solve.genetic.GeneticAlgorithm: Sort the chromosomes.
sortPoints() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Sort the points.
Span - Class in org.encog.bot.browse.range: A document range that specifies a span tag, and any embedded tags.
Span(WebPage) - Constructor for class org.encog.bot.browse.range.Span: Construct a span range from the specified web page.
SPECIAL_CHAR_LIMIT - Static variable in class org.encog.util.http.URLUtility: Beyond this number are special chars.
SQLNeuralDataSet - Class in org.encog.neural.data.sql: A dataset based on a SQL query.
SQLNeuralDataSet(Connection, String, int, int) - Constructor for class org.encog.neural.data.sql.SQLNeuralDataSet: Create a SQLNeuralDataSet based on the specified connection.
SQLNeuralDataSet(String, int, int, String, String, String, String) - Constructor for class org.encog.neural.data.sql.SQLNeuralDataSet: Construct a SQL dataset.
SQLNeuralDataSet.SQLNeuralIterator - Class in org.encog.neural.data.sql: Iterator used to iterate over SQL results.
SQLNeuralDataSet.SQLNeuralIterator() - Constructor for class org.encog.neural.data.sql.SQLNeuralDataSet.SQLNeuralIterator: Construct an iterator.
sqrt(double) - Static method in class org.encog.util.math.BoundMath: Calculate the square root.
START_MOMENTUM - Static variable in class org.encog.neural.networks.training.strategy.SmartMomentum: The starting momentum.
START_X - Static variable in class org.encog.neural.pattern.PatternConst: The starting x-coordinate.
START_Y - Static variable in class org.encog.neural.pattern.PatternConst: The starting y-coordinate.
StatusReportable - Interface in org.encog: This class allows for Encog jobs to report their current status, as they run.
stimulateNeuron(double, Layer, int) - Method in class org.encog.neural.prune.PruneSelective: Stimulate the specified neuron by the specified percent.
stimulateWeakNeurons(Layer, int, double) - Method in class org.encog.neural.prune.PruneSelective: Stimulate weaker neurons on a layer.
stopConsoleLogging() - Static method in class org.encog.util.logging.Logging: Stop logging to the console.
StopTrainingStrategy - Class in org.encog.neural.networks.training.strategy: This strategy will indicate once training is no longer improving the neural network by a specified amount, over a specified number of cycles.
StopTrainingStrategy() - Constructor for class org.encog.neural.networks.training.strategy.StopTrainingStrategy: Construct the strategy with default options.
StopTrainingStrategy(double, int) - Constructor for class org.encog.neural.networks.training.strategy.StopTrainingStrategy: Construct the strategy with the specified parameters.
Strategy - Interface in org.encog.neural.networks.training: Training strategies can be added to training algorithms.
string2double(String) - Static method in class org.encog.util.math.Convert: Convert a string to a double.
string2int(String) - Static method in class org.encog.util.math.Convert: Convert a string to an int.
stripTags(String) - Static method in class org.encog.bot.BotUtil: Strip any HTML or XML tags from the specified string.
subtract(Matrix, Matrix) - Static method in class org.encog.matrix.MatrixMath: Return the results of subtracting one matrix from another.
sum() - Method in class org.encog.matrix.Matrix: Sum all of the values in the matrix.
Synapse - Interface in org.encog.neural.networks.synapse: A synapse is the connection between two layers of a neural network.
SynapseComparator - Class in org.encog.neural.networks.structure: Used to compare the order of synapses.
SynapseComparator(NeuralStructure) - Constructor for class org.encog.neural.networks.structure.SynapseComparator: Construct a layer comparator.
SynapseType - Enum in org.encog.neural.networks.synapse: Specifies the type of synapse to be created.

T

Tag - Class in org.encog.parse.tags: HTMLTag: This class holds a single HTML tag.
Tag() - Constructor for class org.encog.parse.tags.Tag
Tag.Type - Enum in org.encog.parse.tags: Tag types.
TAG_ACTIVATION - Static variable in class org.encog.persist.persistors.BasicLayerPersistor: The activation function tag.
TAG_F1 - Static variable in class org.encog.neural.pattern.ART1Pattern: The tag for the F1 layer.
TAG_F1 - Static variable in class org.encog.neural.pattern.BAMPattern: The tag for the F1 layer.
TAG_F2 - Static variable in class org.encog.neural.pattern.ART1Pattern: The tag for the F2 layer.
TAG_F2 - Static variable in class org.encog.neural.pattern.BAMPattern: The tag for the F2 layer.
TAG_IDEAL - Static variable in class org.encog.persist.persistors.BasicNeuralDataSetPersistor: THe ideal tag.
TAG_INPUT - Static variable in class org.encog.neural.networks.BasicNetwork: Tag used for the input layer.
TAG_INPUT - Static variable in class org.encog.persist.persistors.BasicNeuralDataSetPersistor: The input tag.
TAG_INSTAR - Static variable in class org.encog.neural.pattern.CPNPattern: The tag for the INSTAR layer.
TAG_ITEM - Static variable in class org.encog.persist.persistors.BasicNeuralDataSetPersistor: The item tag.
TAG_ITEM - Static variable in class org.encog.persist.persistors.TrainingContinuationPersistor: An item tag.
TAG_ITEMS - Static variable in class org.encog.persist.persistors.TrainingContinuationPersistor: The items tag.
TAG_LAYER - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The layer synapse.
TAG_LAYERS - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The layers tag.
TAG_LOGIC - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The logic tag.
TAG_OBJECTS - Static variable in class org.encog.persist.PersistReader: The objects tag.
TAG_OUTPUT - Static variable in class org.encog.neural.networks.BasicNetwork: Tag used for the output layer.
TAG_OUTSTAR - Static variable in class org.encog.neural.pattern.CPNPattern: The tag for the OUTSTAR layer.
TAG_PROPERTIES - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The properties tag.
TAG_PROPERTIES - Static variable in class org.encog.persist.persistors.PropertyDataPersistor: The properties tag.
TAG_PROPERTY - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The property tag.
TAG_PROPERTY - Static variable in class org.encog.persist.persistors.PropertyDataPersistor: The property tag.
TAG_SYNAPSE - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The synapse tag.
TAG_SYNAPSES - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The synapses tag.
TAG_TAG - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The tag tag.
TAG_TAGS - Static variable in class org.encog.persist.persistors.BasicNetworkPersistor: The tags tag.
TAG_WEIGHTS - Static variable in class org.encog.persist.persistors.WeightedSynapsePersistor: The weights tag.
TagConst - Class in org.encog.parse.tags: Constants to use while parsing the tags.
TagDataUnit - Class in org.encog.bot.dataunit: A data unit that holds a tag.
TagDataUnit() - Constructor for class org.encog.bot.dataunit.TagDataUnit
tagLayer(String, Layer) - Method in class org.encog.neural.networks.BasicNetwork: Tag a layer.
TemporalDataDescription - Class in org.encog.neural.data.temporal: This class describes one unit of input, or output, to a temporal neural network.
TemporalDataDescription(ActivationFunction, double, double, TemporalDataDescription.Type, boolean, boolean) - Constructor for class org.encog.neural.data.temporal.TemporalDataDescription: Construct a data description item.
TemporalDataDescription(ActivationFunction, TemporalDataDescription.Type, boolean, boolean) - Constructor for class org.encog.neural.data.temporal.TemporalDataDescription: Construct a data description with an activation function, but no range.
TemporalDataDescription(TemporalDataDescription.Type, boolean, boolean) - Constructor for class org.encog.neural.data.temporal.TemporalDataDescription: Construct a data description with no activation function or range.
TemporalDataDescription.Type - Enum in org.encog.neural.data.temporal: The type of data requested.
TemporalError - Exception in org.encog.neural.data.temporal: Error occured processing temporal data.
TemporalError(String) - Constructor for exception org.encog.neural.data.temporal.TemporalError: Construct a message exception.
TemporalError(Throwable) - Constructor for exception org.encog.neural.data.temporal.TemporalError: Construct an exception that holds another exception.
TemporalNeuralDataSet - Class in org.encog.neural.data.temporal: This class implements a temporal neural data set.
TemporalNeuralDataSet(int, int) - Constructor for class org.encog.neural.data.temporal.TemporalNeuralDataSet: Construct a dataset.
TemporalPoint - Class in org.encog.neural.data.temporal: A temporal point is all of the data captured at one point in time to be used for prediction.
TemporalPoint(int) - Constructor for class org.encog.neural.data.temporal.TemporalPoint: Construct a temporal point of the specified size.
TextData - Class in org.encog.neural.data: An Encog object that can hold text data.
TextData() - Constructor for class org.encog.neural.data.TextData
TextDataPersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the TextData class.
TextDataPersistor() - Constructor for class org.encog.persist.persistors.TextDataPersistor
TextDataUnit - Class in org.encog.bot.dataunit: A data unit that holds text.
TextDataUnit() - Constructor for class org.encog.bot.dataunit.TextDataUnit
ThermalLogic - Class in org.encog.neural.networks.logic: Provides the neural logic for thermal networks.
ThermalLogic() - Constructor for class org.encog.neural.networks.logic.ThermalLogic
throwError(String) - Static method in class org.encog.persist.EncogPersistedCollection: Throw and log an error.
TickerSymbol - Class in org.encog.neural.data.market: Holds a ticker symbol and exchange.
TickerSymbol(String) - Constructor for class org.encog.neural.data.market.TickerSymbol: Construct a ticker symbol with no exchange.
TickerSymbol(String, String) - Constructor for class org.encog.neural.data.market.TickerSymbol: Construct a ticker symbol with exchange.
TIMEOUT - Static variable in class org.encog.solve.genetic.GeneticAlgorithm: Threadpool timeout.
TimeSpan - Class in org.encog.util.time: A timespan between two Dates.
TimeSpan(Date, Date) - Constructor for class org.encog.util.time.TimeSpan: Construct a time span.
TimeUnit - Enum in org.encog.util.time: Time units.
TimeUnitNames - Interface in org.encog.util.time: Get the name or code for a time unit.
toArray(double) - Static method in class org.encog.neural.activation.ActivationUtil: Take a single value and create an array that holds it.
toBinary(double) - Static method in class org.encog.matrix.BiPolarUtil: Convert bipolar to binary.
toBiPolar(double) - Static method in class org.encog.matrix.BiPolarUtil: Convert binary to bipolar.
toList(CSVFormat, StringBuilder, double[]) - Static method in class org.encog.util.csv.NumberList: Convert an array of doubles to a comma separated list.
toNormalizedBinary(double) - Static method in class org.encog.matrix.BiPolarUtil: Convert to binary and normalize.
TOO_BIG - Static variable in class org.encog.util.math.BoundNumbers: Too big of a number.
TOO_SMALL - Static variable in class org.encog.util.math.BoundNumbers: Too small of a number.
toPackedArray() - Method in class org.encog.matrix.Matrix: Convert the matrix into a packed array.
toString() - Method in class org.encog.bot.browse.Address
toString() - Method in class org.encog.bot.browse.range.Div
toString() - Method in class org.encog.bot.browse.range.DocumentRange
toString() - Method in class org.encog.bot.browse.range.Form
toString() - Method in class org.encog.bot.browse.range.Input
toString() - Method in class org.encog.bot.browse.range.Link
toString() - Method in class org.encog.bot.browse.range.Span
toString() - Method in class org.encog.bot.browse.WebPage
toString() - Method in class org.encog.bot.dataunit.CodeDataUnit
toString() - Method in class org.encog.bot.dataunit.TagDataUnit
toString() - Method in class org.encog.bot.dataunit.TextDataUnit
toString() - Method in class org.encog.bot.rss.RSS: Convert the object to a String.
toString() - Method in class org.encog.bot.rss.RSSItem: Convert the object to a String.
toString() - Method in class org.encog.matrix.Matrix
toString() - Method in class org.encog.neural.data.basic.BasicNeuralData: Return a string representation of this object.
toString() - Method in class org.encog.neural.data.basic.BasicNeuralDataPair: Convert the object to a string.
toString() - Method in class org.encog.neural.data.bipolar.BiPolarNeuralData
toString() - Method in class org.encog.neural.data.image.ImageNeuralData: Return a string representation of this object.
toString() - Method in class org.encog.neural.data.temporal.TemporalPoint: Convert this point to string form.
toString() - Method in class org.encog.neural.networks.BasicNetwork
toString() - Method in class org.encog.neural.networks.layers.BasicLayer
toString() - Method in interface org.encog.neural.networks.Network
toString() - Method in class org.encog.neural.networks.synapse.BasicSynapse
toString() - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining
toString() - Method in class org.encog.parse.tags.read.ReadTags
toString() - Method in class org.encog.parse.tags.Tag: Convert this tag back into string form, with the beginning < and ending >.
toString() - Method in class org.encog.persist.DirectoryEntry
toString() - Method in class org.encog.solve.genetic.Chromosome: Convert the chromosome to a string.
Train - Interface in org.encog.neural.networks.training: Interface for all neural network training methods.
TrainAdaline - Class in org.encog.neural.networks.training.simple: Train an ADALINE neural network.
TrainAdaline(BasicNetwork, NeuralDataSet, double) - Constructor for class org.encog.neural.networks.training.simple.TrainAdaline: Construct an ADALINE trainer.
trainConsole(BasicNetwork, NeuralDataSet, int) - Static method in class org.encog.util.simple.EncogUtility: Train the neural network, using SCG training, and output status to the console.
trainConsole(Train, BasicNetwork, NeuralDataSet, int) - Static method in class org.encog.util.simple.EncogUtility: Train the network, using the specified training algorithm, and send the output to the console.
trainDialog(BasicNetwork, NeuralDataSet) - Static method in class org.encog.util.simple.EncogUtility: Train using SCG and display progress to a dialog box.
trainDialog(Train, BasicNetwork, NeuralDataSet) - Static method in class org.encog.util.simple.EncogUtility: Train, using the specified training method, display progress to a dialog box.
TrainingContinuation - Class in org.encog.neural.networks.training.propagation: Allows training to be continued.
TrainingContinuation() - Constructor for class org.encog.neural.networks.training.propagation.TrainingContinuation
TrainingContinuationPersistor - Class in org.encog.persist.persistors: Persist a training continuation persistor.
TrainingContinuationPersistor() - Constructor for class org.encog.persist.persistors.TrainingContinuationPersistor
TrainingDialog - Class in org.encog.util.simple: Display a training dialog.
TrainingDialog() - Constructor for class org.encog.util.simple.TrainingDialog: Construct the training dialog.
TrainingError - Exception in org.encog.neural.networks.training: Thrown when a training error occurs.
TrainingError(String) - Constructor for exception org.encog.neural.networks.training.TrainingError: Construct a message exception.
TrainingError(Throwable) - Constructor for exception org.encog.neural.networks.training.TrainingError: Construct an exception that holds another exception.
TrainingSetScore - Class in org.encog.neural.networks.training: Calculate a score based on a training set.
TrainingSetScore(NeuralDataSet) - Constructor for class org.encog.neural.networks.training.TrainingSetScore: Construct a training set score calculation.
TrainInstar - Class in org.encog.neural.networks.training.cpn: Used for Instar training of a CPN neural network.
TrainInstar(BasicNetwork, NeuralDataSet, double) - Constructor for class org.encog.neural.networks.training.cpn.TrainInstar: Construct the instar training object.
TrainOutstar - Class in org.encog.neural.networks.training.cpn: Used for Instar training of a CPN neural network.
TrainOutstar(BasicNetwork, NeuralDataSet, double) - Constructor for class org.encog.neural.networks.training.cpn.TrainOutstar: Construct the outstar trainer.
trainPattern(NeuralData) - Method in class org.encog.neural.networks.training.competitive.CompetitiveTraining: Train the specified pattern.
trainToError(BasicNetwork, NeuralDataSet, double) - Static method in class org.encog.util.simple.EncogUtility: Train the network, to a specific error, send the output to the console.
trainToError(Train, BasicNetwork, NeuralDataSet, double) - Static method in class org.encog.util.simple.EncogUtility: Train to a specific error, using the specified training method, send the output to the console.
transpose(Matrix) - Static method in class org.encog.matrix.MatrixMath: Return the transposition of a matrix.
TRYS - Static variable in class org.encog.util.benchmark.Evaluate: How many times to try.
twoPassesNeeded() - Method in class org.encog.normalize.DataNormalization
TYPE_BASIC_LAYER - Static variable in class org.encog.persist.EncogPersistedCollection: The type is BasicLayer.
TYPE_BASIC_NET - Static variable in class org.encog.persist.EncogPersistedCollection: The type is BasicNetwork.
TYPE_CONTEXT_LAYER - Static variable in class org.encog.persist.EncogPersistedCollection: The type is ContextLayer.
TYPE_DIRECT_SYNAPSE - Static variable in class org.encog.persist.EncogPersistedCollection: The type is DirectSynapse.
TYPE_NORMALIZATION - Static variable in class org.encog.persist.EncogPersistedCollection: The type is ParseTemplate.
TYPE_ONE2ONE_SYNAPSE - Static variable in class org.encog.persist.EncogPersistedCollection: The type is OneToOneSynapse.
TYPE_PROPERTY - Static variable in class org.encog.persist.EncogPersistedCollection: The type is PropertyData.
TYPE_RADIAL_BASIS_LAYER - Static variable in class org.encog.persist.EncogPersistedCollection: The type is RadialBasisFunctionLayer.
TYPE_TEXT - Static variable in class org.encog.persist.EncogPersistedCollection: The type is TextData.
TYPE_TRAINING - Static variable in class org.encog.persist.EncogPersistedCollection: The type is TrainingData.
TYPE_TRAINING_CONTINUATION - Static variable in class org.encog.persist.EncogPersistedCollection: For training continuation.
TYPE_WEIGHTED_SYNAPSE - Static variable in class org.encog.persist.EncogPersistedCollection: The type is WeightedSynapse.
TYPE_WEIGHTLESS_SYNAPSE - Static variable in class org.encog.persist.EncogPersistedCollection: The type is WeightlessSynapse.

U

UnionNeuralDataSet - Class in org.encog.neural.data.union: A UnionNeuralDataSet is used to create a compound data set that is made up of other data sets.
UnionNeuralDataSet(int, int) - Constructor for class org.encog.neural.data.union.UnionNeuralDataSet: Construct the union data set.
UnionNeuralDataSet.UnionIterator - Class in org.encog.neural.data.union: The iterator used to access the UnionNeuralDataSet.
UnionNeuralDataSet.UnionIterator() - Constructor for class org.encog.neural.data.union.UnionNeuralDataSet.UnionIterator: Construct the union iterator.
UPDATE_VALUES - Static variable in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagation: Continuation tag for the last values.
updateError(double[], double[]) - Method in class org.encog.util.ErrorCalculation: Called to update for each number that should be checked.
updateError(NeuralData, NeuralData) - Method in class org.encog.util.ErrorCalculation: Update the error.
updateGenes() - Method in class org.encog.neural.networks.training.genetic.NeuralChromosome: Copy the network to the genes.
updateNetwork() - Method in class org.encog.neural.networks.training.genetic.NeuralChromosome: Copy the genes to the network.
updateProperties(String, String, String) - Method in class org.encog.persist.EncogPersistedCollection: Update any header properties for an Encog object, for example, a rename.
URLUtility - Class in org.encog.util.http: URLUtility: A set of useful utilities for processing URL's.

V

validateNetworkForTraining(BasicNetwork, NeuralDataSet) - Static method in class org.encog.util.EncogValidate
valueOf(String) - Static method in enum org.encog.bot.browse.range.Form.Method: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.encog.neural.data.market.MarketDataType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.encog.neural.data.temporal.TemporalDataDescription.Type: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.encog.neural.networks.synapse.SynapseType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.encog.neural.prune.NetworkPattern: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.encog.parse.tags.Tag.Type: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum org.encog.util.time.TimeUnit: Returns the enum constant of this type with the specified name.
values() - Static method in enum org.encog.bot.browse.range.Form.Method: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.encog.neural.data.market.MarketDataType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.encog.neural.data.temporal.TemporalDataDescription.Type: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.encog.neural.networks.synapse.SynapseType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.encog.neural.prune.NetworkPattern: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.encog.parse.tags.Tag.Type: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum org.encog.util.time.TimeUnit: Returns an array containing the constants of this enum type, in the order they are declared.
vectorLength(Matrix) - Static method in class org.encog.matrix.MatrixMath: Calculate the length of a vector.
vectorProduct(double[], double[]) - Static method in class org.encog.util.EncogArray: Calculate the product of two vectors (a scalar value).
VERSION - Static variable in class org.encog.Encog: The current engog version, this should be read from the properties.

W

WebPage - Class in org.encog.bot.browse: Holds a web page that was loaded by the Browse class.
WebPage() - Constructor for class org.encog.bot.browse.WebPage
WeightedSynapse - Class in org.encog.neural.networks.synapse: A fully-connected weight based synapse.
WeightedSynapse() - Constructor for class org.encog.neural.networks.synapse.WeightedSynapse: Simple default constructor.
WeightedSynapse(Layer, Layer) - Constructor for class org.encog.neural.networks.synapse.WeightedSynapse: Construct a weighted synapse between the two layers.
WeightedSynapsePersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the ActivationBiPolar class.
WeightedSynapsePersistor() - Constructor for class org.encog.persist.persistors.WeightedSynapsePersistor
WeightlessSynapse - Class in org.encog.neural.networks.synapse: A fully connected synapse that simply sums all input to each neuron, no weights are applied.
WeightlessSynapse() - Constructor for class org.encog.neural.networks.synapse.WeightlessSynapse: Simple default constructor.
WeightlessSynapse(Layer, Layer) - Constructor for class org.encog.neural.networks.synapse.WeightlessSynapse: Construct a weighted synapse between the two layers.
WeightlessSynapsePersistor - Class in org.encog.persist.persistors: The Encog persistor used to persist the WeightlessSynapse class.
WeightlessSynapsePersistor() - Constructor for class org.encog.persist.persistors.WeightlessSynapsePersistor
winner(NeuralData) - Method in class org.encog.neural.networks.BasicNetwork: Determine the winner for the specified input.
winner(NeuralData) - Method in interface org.encog.neural.networks.Network: Determine the winner for the specified input.
winner(NeuralData) - Method in class org.encog.neural.networks.training.cpn.FindCPN: Calculate the winning neuron from the data, this is the neuron that has the highest output.
write(double[], int) - Method in interface org.encog.normalize.target.NormalizationStorage: Write an array.
write(double[], int) - Method in class org.encog.normalize.target.NormalizationStorageArray1D: Write an array.
write(double[], int) - Method in class org.encog.normalize.target.NormalizationStorageArray2D: Write an array.
write(double[], int) - Method in class org.encog.normalize.target.NormalizationStorageCSV: Write an array.
write(double[], int) - Method in class org.encog.normalize.target.NormalizationStorageNeuralDataSet: Write an array.
writeHeader() - Method in class org.encog.persist.PersistWriter: Write the header for the Encog file.
writeln(String) - Method in class org.encog.util.http.FormUtility: Write a string, with a carriage return and linefeed.
writeObject(EncogPersistedObject) - Method in class org.encog.persist.PersistWriter: Write an object.
WriteTags - Class in org.encog.parse.tags.write: Class used to write out tags, such as XML or HTML.
WriteTags(OutputStream) - Constructor for class org.encog.parse.tags.write.WriteTags: Construct an object to write tags.
WriteXML - Class in org.encog.parse.tags.write: Contains specifics to writing XML.
WriteXML(OutputStream) - Constructor for class org.encog.parse.tags.write.WriteXML: Construct an object to write an XML file.

X

XML2Object - Class in org.encog.persist.persistors.generic: A generic class used to take an XML segment and produce an object for it.
XML2Object() - Constructor for class org.encog.persist.persistors.generic.XML2Object
XMLNeuralDataSet - Class in org.encog.neural.data.xml: A data source that reads XML files.
XMLNeuralDataSet(String, int, int, String, String, String, String) - Constructor for class org.encog.neural.data.xml.XMLNeuralDataSet: Construct an XML neural data set.
XMLNeuralDataSet.XMLNeuralIterator - Class in org.encog.neural.data.xml: An iterator designed to read from XML files.
XMLNeuralDataSet.XMLNeuralIterator() - Constructor for class org.encog.neural.data.xml.XMLNeuralDataSet.XMLNeuralIterator: Construct an iterator to read the XML data.

Y

YahooFinanceLoader - Class in org.encog.neural.data.market.loader: This class loads financial data from Yahoo.
YahooFinanceLoader() - Constructor for class org.encog.neural.data.market.loader.YahooFinanceLoader
YahooSearch - Class in org.encog.util: YahooSearch: Perform a search using Yahoo.
YahooSearch() - Constructor for class org.encog.util.YahooSearch
YEARS_CENTURY - Static variable in class org.encog.util.time.TimeSpan: Years in a century.
YEARS_MIL - Static variable in class org.encog.util.time.TimeSpan: Years in a mil.
YEARS_SCORE - Static variable in class org.encog.util.time.TimeSpan: Years in a score.

Z

ZAxisGroup - Class in org.encog.normalize.output.zaxis: Used to group Z-Axis fields together.
ZAxisGroup() - Constructor for class org.encog.normalize.output.zaxis.ZAxisGroup

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