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The Encog Project

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A

accumulateThresholdGradient(int, double) - Method in class org.encog.neural.networks.training.propagation.PropagationLevel: Call this method to accumulate the threshold gradients during a batch.
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.
addListener(ExtractListener) - Method in class org.encog.bot.browse.extract.BasicExtract: Add a listener for the extraction.
addListener(ExtractListener) - Method in interface org.encog.bot.browse.extract.Extract: Add a listener for the extraction.
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.
arrayToNetwork(Double[], BasicNetwork) - Static method in class org.encog.neural.networks.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
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
ATTRIBUTE_NAME - Static variable in class org.encog.persist.persistors.PropertyDataPersistor: 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
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.

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
BackpropagationMethod - Class in org.encog.neural.networks.training.propagation.back: This class implements the specifics of how the backpropagation algorithm is used.
BackpropagationMethod(double, double) - Constructor for class org.encog.neural.networks.training.propagation.back.BackpropagationMethod: Construct a back propagation method.
backwardPass(NeuralData) - Method in class org.encog.neural.networks.training.propagation.PropagationUtil: Calculate the error for the recognition just done.
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
BasicExtract - Class in org.encog.bot.browse.extract: Implements the basic functionality that most extractors will need to implement.
BasicExtract() - Constructor for class org.encog.bot.browse.extract.BasicExtract
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(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(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 interface org.encog.util.math.rbf.RadialBasisFunction: 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).
calculateCost() - Method in class org.encog.neural.networks.training.genetic.TrainingSetNeuralChromosome: Calculate the cost for this chromosome.
calculateCost() - Method in class org.encog.solve.genetic.Chromosome: Called to calculate the cost for this chromosome.
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.
calculateError(NeuralOutputHolder, PropagationLevel, PropagationLevel) - Method in class org.encog.neural.networks.training.propagation.back.BackpropagationMethod: Calculate the error between these two levels.
calculateError(NeuralOutputHolder, PropagationLevel, PropagationLevel) - Method in class org.encog.neural.networks.training.propagation.CalculatePartialDerivative: Calculate the partial derivative of the error for a layer.
calculateError(NeuralOutputHolder, PropagationLevel, PropagationLevel) - Method in class org.encog.neural.networks.training.propagation.manhattan.ManhattanPropagationMethod: Calculate the error between these two levels.
calculateError(NeuralOutputHolder, PropagationLevel, PropagationLevel) - Method in interface org.encog.neural.networks.training.propagation.PropagationMethod: Calculate the error between these two levels.
calculateError(NeuralOutputHolder, PropagationLevel, PropagationLevel) - Method in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagationMethod: Calculate the error between these two levels.
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.
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.
CalculatePartialDerivative - Class in org.encog.neural.networks.training.propagation: Class that is used to calculate the partial derivatives for the error for individual layers of a neural network.
CalculatePartialDerivative() - Constructor for class org.encog.neural.networks.training.propagation.CalculatePartialDerivative
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.
calculateStartIndex() - Method in class org.encog.neural.data.temporal.TemporalNeuralDataSet: Calculate the index to start at.
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.
checkInputSize(NeuralData) - Method in class org.encog.neural.networks.BasicNetwork: Check that the input size is acceptable, if it does not match the input layer, then throw an error.
checkInputSize(NeuralData) - Method in interface org.encog.neural.networks.Network: Check that the input size is acceptable, if it does not match the input layer, then throw an error.
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
collect() - Method in class org.encog.neural.networks.training.propagation.multi.GradientMap: Collect the gradient descents from all levels and synapses and place them in the master training utility.
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.
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(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.
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.
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.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.
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.multi.MultiPropagation: 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.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.
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.
determineError() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealing: Determine the error of the current weights and thresholds.
determineError() - Method in class org.encog.neural.networks.training.anneal.NeuralSimulatedAnnealingHelper: Used to pass the determineError call on to the parent object.
determineError() - Method in class org.encog.neural.networks.training.anneal.NeuralTrainingSetSimulatedAnnealing: Determine the error of the current weights and thresholds.
determineError() - Method in class org.encog.solve.anneal.SimulatedAnnealing: Subclasses should provide a method that evaluates the error for the current solution.
determineNeuronSignificance(Layer, int) - Method in class org.encog.neural.prune.PruneSelective: Determine the significance of the neuron.
determinePreviousSynapses() - Method in class org.encog.neural.networks.training.propagation.PropagationLevel: Determine the previous synapses from this level.
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.
distribute(Object) - Method in class org.encog.bot.browse.extract.BasicExtract: Distribute an object to the listeners.
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.
downsample(Downsample, boolean, int, int) - 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(int, int) - Method in interface org.encog.util.downsample.Downsample: Downsample the image to the specified height and width.
downSample(int, int) - Method in class org.encog.util.downsample.SimpleIntensityDownsample: Called to downsample the image and store it in the down sample component.
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.
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.
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.
EncogFormatter - Class in org.encog.util.logging: A simple formatter for logging.
EncogFormatter() - Constructor for class org.encog.util.logging.EncogFormatter
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.
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
equals(Matrix) - 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.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.
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.
Extract - Interface in org.encog.bot.browse.extract: Provides the basic interface that any extractor must support.
extract(WebPage) - Method in interface org.encog.bot.browse.extract.Extract: Extract data from the web 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.
extractList(WebPage) - Method in class org.encog.bot.browse.extract.BasicExtract: Extract from the web page and return the results as a list.
extractList(WebPage) - Method in interface org.encog.bot.browse.extract.Extract: Extract from the web page and return the results as a list.
ExtractListener - Interface in org.encog.bot.browse.extract: The ExtractListener interface defines a class that can receive extraction events as an extraction process occurs.

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.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.SimpleIntensityDownsample: 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.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.
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(LogRecord) - Method in class org.encog.util.logging.EncogFormatter: Format the log record.
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.
forwardPass(NeuralData) - Method in class org.encog.neural.networks.training.propagation.PropagationUtil: Perform the forward pass and determine each layer's output.
foundData(Object) - Method in interface org.encog.bot.browse.extract.ExtractListener: Notify that some data has been extracted.
foundData(Object) - Method in class org.encog.bot.browse.extract.ListExtractListener: Called when a word is found, add it to the list.
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.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.
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(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
getAccMatrixGradients() - Method in class org.encog.neural.networks.training.propagation.PropagationSynapse
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
getActivationFunction() - Method in class org.encog.neural.networks.layers.RadialBasisFunctionLayer
getActual(int) - Method in class org.encog.neural.networks.training.propagation.PropagationLevel: Get the actual output from the specified neuron.
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.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
getBatchSize() - Method in class org.encog.neural.networks.training.propagation.Propagation
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
getCatchAll() - Method in class org.encog.normalize.output.mapped.OutputFieldEncode
getCenter() - Method in class org.encog.util.math.rbf.GaussianFunction
getCenter() - Method in interface org.encog.util.math.rbf.RadialBasisFunction
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.persist.EncogMemoryCollection
getContext() - Method in class org.encog.neural.networks.layers.ContextLayer
getCost() - Method in class org.encog.solve.genetic.Chromosome
getCount() - Method in class org.encog.normalize.segregate.IntegerBalanceSegregator
getCSVFormat() - Method in class org.encog.normalize.DataNormalization
getCurrentIndex() - Method in class org.encog.normalize.segregate.index.IndexSegregator
getCurrentPage() - Method in class org.encog.bot.browse.Browser
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
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.
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.
getDelta(int) - Method in class org.encog.neural.networks.training.propagation.PropagationLevel: The deltas, or differences, between the ideal and actual.
getDeltas() - Method in class org.encog.neural.networks.training.propagation.PropagationLevel
getDeltas() - Method in class org.encog.neural.networks.training.propagation.PropagationSynapse
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.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
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.
getDownSampleBottom() - Method in interface org.encog.util.downsample.Downsample
getDownSampleBottom() - Method in class org.encog.util.downsample.SimpleIntensityDownsample
getDownSampleLeft() - Method in interface org.encog.util.downsample.Downsample
getDownSampleLeft() - Method in class org.encog.util.downsample.SimpleIntensityDownsample
getDownSampleRight() - Method in interface org.encog.util.downsample.Downsample
getDownSampleRight() - Method in class org.encog.util.downsample.SimpleIntensityDownsample
getDownSampleTop() - Method in interface org.encog.util.downsample.Downsample
getDownSampleTop() - Method in class org.encog.util.downsample.SimpleIntensityDownsample
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.multi.MPROPWorker
getError() - Method in interface org.encog.neural.networks.training.Train: Get the current error percent from the training.
getError() - Method in class org.encog.solve.anneal.SimulatedAnnealing
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
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
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
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
getImage() - Method in interface org.encog.util.downsample.Downsample
getImage() - Method in class org.encog.util.downsample.SimpleIntensityDownsample
getImageHeight() - Method in interface org.encog.util.downsample.Downsample
getImageHeight() - Method in class org.encog.util.downsample.SimpleIntensityDownsample
getImageWidth() - Method in interface org.encog.util.downsample.Downsample
getImageWidth() - Method in class org.encog.util.downsample.SimpleIntensityDownsample
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.neural.networks.logic.ART1Logic
getL() - Method in class org.encog.neural.pattern.ART1Pattern
getLastMatrixGradients() - Method in class org.encog.neural.networks.training.propagation.PropagationSynapse
getLastThresholdGradent(int) - Method in class org.encog.neural.networks.training.propagation.PropagationLevel: Get the specified threshold gradient, from the last iteration of training.
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.NeuralStructure
getLayers() - Method in class org.encog.neural.networks.training.propagation.PropagationLevel
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
getLevelMap() - Method in class org.encog.neural.networks.training.propagation.multi.GradientMap
getLevels() - Method in class org.encog.neural.networks.training.propagation.multi.GradientMap
getLevels() - Method in class org.encog.neural.networks.training.propagation.PropagationUtil
getLink() - Method in class org.encog.bot.rss.RSSItem: Get the hyperlink.
getList() - Method in class org.encog.bot.browse.extract.ListExtractListener
getListeners() - Method in class org.encog.bot.browse.extract.BasicExtract
getListeners() - Method in interface org.encog.bot.browse.extract.Extract
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() - 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
getMethod() - Method in class org.encog.neural.networks.training.propagation.PropagationUtil
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.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.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.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.multi.MultiPropagation
getNetwork() - Method in class org.encog.neural.networks.training.propagation.Propagation
getNetwork() - Method in class org.encog.neural.networks.training.propagation.PropagationUtil: Get the current best neural network.
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
getNeuronCount() - Method in class org.encog.neural.networks.training.propagation.PropagationLevel
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.
getNext() - Method in class org.encog.neural.networks.training.propagation.multi.MPROPWorker
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
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
getOutgoing() - Method in class org.encog.neural.networks.training.propagation.PropagationLevel
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
getOutputHolder() - Method in class org.encog.neural.networks.training.propagation.PropagationUtil
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 interface org.encog.util.math.rbf.RadialBasisFunction
getPercentToMate() - Method in class org.encog.solve.genetic.GeneticAlgorithm: Get the percent to mate.
getPixelMap() - Method in interface org.encog.util.downsample.Downsample
getPixelMap() - Method in class org.encog.util.downsample.SimpleIntensityDownsample
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.NeuralStructure: Get the previous layers from the specified layer.
getPreviousSynapses(Layer) - Method in class org.encog.neural.networks.NeuralStructure: Get the previous synapses.
getPropagationUtil() - Method in class org.encog.neural.networks.training.propagation.multi.MPROPWorker
getPropagationUtil() - Method in class org.encog.neural.networks.training.propagation.Propagation
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.
getRadialBasisFunction() - Method in class org.encog.neural.networks.layers.RadialBasisFunctionLayer
getRatioX() - Method in interface org.encog.util.downsample.Downsample
getRatioX() - Method in class org.encog.util.downsample.SimpleIntensityDownsample
getRatioY() - Method in interface org.encog.util.downsample.Downsample
getRatioY() - Method in class org.encog.util.downsample.SimpleIntensityDownsample
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
getSampleSize() - Method in class org.encog.normalize.segregate.index.IndexSampleSegregator
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
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
getSynapse() - Method in class org.encog.neural.networks.training.propagation.PropagationSynapse
getSynapseMap() - Method in class org.encog.neural.networks.training.propagation.multi.GradientMap
getSynapses() - Method in class org.encog.neural.networks.NeuralStructure
getSynapses() - Method in class org.encog.neural.networks.training.propagation.multi.GradientMap
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.
getThresholdDelta(int) - Method in class org.encog.neural.networks.training.propagation.PropagationLevel: Get the specified threshold value's delta.
getThresholdGradient(int) - Method in class org.encog.neural.networks.training.propagation.PropagationLevel: Get a specific threshold gradient.
getThresholdGradients() - Method in class org.encog.neural.networks.training.propagation.PropagationLevel
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
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
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
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.neural.networks.training.competitive.neighborhood.NeighborhoodBubble
getWidth() - Method in class org.encog.util.ImageSize
getWidth() - Method in class org.encog.util.math.rbf.GaussianFunction
getWidth() - Method in interface org.encog.util.math.rbf.RadialBasisFunction
getWinner() - Method in class org.encog.neural.networks.logic.ART1Logic
getWorkers() - Method in class org.encog.neural.networks.training.propagation.multi.MultiPropagation
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
GradientMap - Class in org.encog.neural.networks.training.propagation.multi: The gradient map is used to track all of the workers and collect their gradient descents into the master neural network for training.
GradientMap(PropagationUtil, MultiPropagation) - Constructor for class org.encog.neural.networks.training.propagation.multi.GradientMap: Construct a mapping between the master network training levels and all of the workers.
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

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.

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(Class<Downsample>, boolean) - 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(PropagationUtil) - Method in class org.encog.neural.networks.training.propagation.back.BackpropagationMethod: Setup this propagation method using the specified propagation class.
init(PropagationUtil) - Method in class org.encog.neural.networks.training.propagation.manhattan.ManhattanPropagationMethod: Init with the specified propagation object.
init(PropagationUtil) - Method in interface org.encog.neural.networks.training.propagation.PropagationMethod: Init with the specified propagation object.
init(PropagationUtil) - Method in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagationMethod: Init with the specified propagation object.
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
IntegerBalanceSegregator(InputField, int) - Constructor for class org.encog.normalize.segregate.IntegerBalanceSegregator
IntegerBalanceSegregator() - Constructor for class org.encog.normalize.segregate.IntegerBalanceSegregator
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
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.
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
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.
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
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.multi.MultiPropagation: Perform one iteration of training.
iteration() - Method in class org.encog.neural.networks.training.propagation.Propagation: Perform one iteration of training.
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

Layer - Interface in org.encog.neural.networks.layers: This interface defines all necessary methods for a neural network layer.
learn() - Method in class org.encog.neural.networks.training.propagation.back.BackpropagationMethod: Modify the weight matrix and thresholds based on the last call to calcError.
learn() - Method in class org.encog.neural.networks.training.propagation.manhattan.ManhattanPropagationMethod: Modify the weight matrix and thresholds based on the last call to calcError.
learn() - Method in interface org.encog.neural.networks.training.propagation.PropagationMethod: Apply the accumulated deltas and learn.
learn() - Method in class org.encog.neural.networks.training.propagation.resilient.ResilientPropagationMethod: Modify the weight matrix and thresholds based on the last call to calcError.
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
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.
ListExtractListener - Class in org.encog.bot.browse.extract: A simple implementation of the ExtractListener interface that will listen for words and add them to a list.
ListExtractListener() - Constructor for class org.encog.bot.browse.extract.ListExtractListener
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.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.

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.
ManhattanPropagationMethod - Class in org.encog.neural.networks.training.propagation.manhattan: Implements the specifics of the Manhattan propagation algorithm.
ManhattanPropagationMethod(double, double) - Constructor for class org.encog.neural.networks.training.propagation.manhattan.ManhattanPropagationMethod: Construct a Manhattan update trainer.
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.
MPROPWorker - Class in org.encog.neural.networks.training.propagation.multi: Worker process for MPROP training.
MPROPWorker(BasicNetwork, Indexable, MultiPropagation, long, long) - Constructor for class org.encog.neural.networks.training.propagation.multi.MPROPWorker: Construct a MPROP worker.
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(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.
MultiPropagation - Class in org.encog.neural.networks.training.propagation.multi: MPROP - Multipropagation Training.
MultiPropagation(BasicNetwork, NeuralDataSet) - Constructor for class org.encog.neural.networks.training.propagation.multi.MultiPropagation: Construct a MPROP trainer that will use the number of available processors plus 1.
MultiPropagation(BasicNetwork, NeuralDataSet, int) - Constructor for class org.encog.neural.networks.training.propagation.multi.MultiPropagation: Construct a multi propagation trainer.
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.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.
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: 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.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() - Constructor for class org.encog.neural.networks.training.genetic.NeuralChromosome
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,