Public Static Fields
  DEFAULT_INITIAL_UPDATE | The starting update for a delta. |
| DEFAULT_MAX_STEP | The maximum amount a delta can reach. |
| DEFAULT_ZERO_TOLERANCE | The default zero tolerance. |
| DELTA_MIN | The minimum delta value for a weight matrix value. |
| NEGATIVE_ETA | The NEGATIVE ETA value. This is specified by the resilient propagation algorithm. This is the percentage by which the deltas are increased by if the partial derivative is less than zero. |
| POSITIVE_ETA | The POSITIVE ETA value. This is specified by the resilient propagation algorithm. This is the percentage by which the deltas are increased by if the partial derivative is greater than zero. |
Public Instance Constructors
ResilientPropagation
|
Overloaded. Initializes a new instance of the ResilientPropagation class. |
Public Instance Properties
 Error (inherited from BasicTraining) | Get the current error percent from the training. |
| InitialUpdate | The initial update amount, set by the constructor. |
| Levels (inherited from Propagation) | The propagation levels. |
| MaxStep | The maximum step, set by the constructor. |
| Network (inherited from Propagation) | Get the current best neural network. |
| OutputHolder (inherited from Propagation) | The output holder being used. |
| Strategies (inherited from BasicTraining) | The strategies to use. |
| Training (inherited from BasicTraining) | The training data to use. |
| ZeroTolerance | The zero tolerance, set by the constructor. |
Public Instance Methods
| AddStrategy (inherited from BasicTraining) | Training strategies can be added to improve the training results. There are a number to choose from, and several can be used at once. |
| BackwardPass (inherited from Propagation) | Calculate the error for the recognition just done. |
| Equals (inherited from Object) | |
| GetHashCode (inherited from Object) | |
| GetType (inherited from Object) | |
| Iteration (inherited from Propagation) | Perform one iteration of training. Note: if you get a StackOverflowError while training, then you have endless recurrent loops. Try inserting no trainable synapses on one side of the loop. |
| PostIteration (inherited from BasicTraining) | Call the strategies after an iteration. |
| PreIteration (inherited from BasicTraining) | Call the strategies before an iteration. |
| ToString (inherited from Object) |
Protected Instance Methods
 Finalize (inherited from Object) | |
| MemberwiseClone (inherited from Object) |
See Also
ResilientPropagation Class | Encog.Neural.Networks.Training.Propagation.Resilient Namespace