Class ILNeuralNetwork.TILNeuralNetworkRPropTrain
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(Automated Syncronization with Documentation) |
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== Description == | == Description == | ||
− | This component is designed to train neural networks using | + | This component is designed to train neural networks using |
− | algorithm. | + | RProp algorithm. |
To use the component set the Neural Network to be trained in | To use the component set the Neural Network to be trained in | ||
the NeuralNetwork property. | the NeuralNetwork property. | ||
+ | |||
+ | |||
+ | |||
+ | <b>Diagram:</b> | ||
+ | |||
+ | [[Image:ILNeuralNetworkRPropTrain_Preview.png]] | ||
== Properties == | == Properties == | ||
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*[[Property ILNeuralNetwork.TILNeuralNetworkTrain.TerminationCriteria|TerminationCriteria]] - Criteria for terminating the training. | *[[Property ILNeuralNetwork.TILNeuralNetworkTrain.TerminationCriteria|TerminationCriteria]] - Criteria for terminating the training. | ||
*[[Property ILNeuralNetwork.TILNeuralNetworkTrain.NormalizeTrainingWeights|NormalizeTrainingWeights]] - Specifies if the weights should be normalized. | *[[Property ILNeuralNetwork.TILNeuralNetworkTrain.NormalizeTrainingWeights|NormalizeTrainingWeights]] - Specifies if the weights should be normalized. | ||
+ | *[[Property ILNeuralNetwork.TILNeuralNetworkTrain.ScaleInputs|ScaleInputs]] - Scales the inputs before the training. | ||
+ | *[[Property ILNeuralNetwork.TILNeuralNetworkTrain.ScaleOutputs|ScaleOutputs]] - Scales the outputs before the training. | ||
== Methods == | == Methods == | ||
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=== Public === | === Public === | ||
*[[Method function ILNeuralNetwork.TILNeuralNetworkTrain.Train(IILTrainingDataArray) : Integer|function Train(AData : IILTrainingDataArray) : Integer]] - Trains the connected neural network. | *[[Method function ILNeuralNetwork.TILNeuralNetworkTrain.Train(IILTrainingDataArray) : Integer|function Train(AData : IILTrainingDataArray) : Integer]] - Trains the connected neural network. | ||
− | *[[Method function ILNeuralNetwork.TILNeuralNetworkTrain.Train( | + | *[[Method function ILNeuralNetwork.TILNeuralNetworkTrain.Train(ISLRealBuffer;ISLRealBuffer) : Integer|function Train(ATraingFeatures : ISLRealBuffer; AResposes : ISLRealBuffer) : Integer]] |
− | *[[Method function ILNeuralNetwork.TILNeuralNetworkTrain.Train( | + | *[[Method function ILNeuralNetwork.TILNeuralNetworkTrain.Train(ISLRealBuffer;ISLRealBuffer;Real) : Integer|function Train(ATraingFeatures : ISLRealBuffer; AResposes : ISLRealBuffer; AWeights : Real) : Integer]] |
*[[Method function ILNeuralNetwork.TILNeuralNetworkTrain.Train(ISLRealBufferArray;ISLRealBufferArray) : Integer|function Train(ATraingFeatures : ISLRealBufferArray; AResposes : ISLRealBufferArray) : Integer]] - Trains the connected neural network. | *[[Method function ILNeuralNetwork.TILNeuralNetworkTrain.Train(ISLRealBufferArray;ISLRealBufferArray) : Integer|function Train(ATraingFeatures : ISLRealBufferArray; AResposes : ISLRealBufferArray) : Integer]] - Trains the connected neural network. | ||
*[[Method function ILNeuralNetwork.TILNeuralNetworkTrain.Train(ISLRealBufferArray;ISLRealBufferArray;ISLRealBuffer) : Integer|function Train(ATraingFeatures : ISLRealBufferArray; AResposes : ISLRealBufferArray; AWeights : ISLRealBuffer) : Integer]] - Trains the connected neural network. | *[[Method function ILNeuralNetwork.TILNeuralNetworkTrain.Train(ISLRealBufferArray;ISLRealBufferArray;ISLRealBuffer) : Integer|function Train(ATraingFeatures : ISLRealBufferArray; AResposes : ISLRealBufferArray; AWeights : ISLRealBuffer) : Integer]] - Trains the connected neural network. | ||
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== Events == | == Events == | ||
*[[Event ILNeuralNetwork.TILNeuralNetworkTrain.OnProgress|OnProgress]] - Training progress notification event. | *[[Event ILNeuralNetwork.TILNeuralNetworkTrain.OnProgress|OnProgress]] - Training progress notification event. | ||
+ | *[[Event ILNeuralNetwork.TILNeuralNetworkTrain.OnError|OnError]] - Occurs on training error. | ||
[[Category:Components]][[Category:Classes]] | [[Category:Components]][[Category:Classes]] |
Revision as of 20:30, 10 June 2013
This is a Beta Read Only version of this page. Please review and send recommendations to mitov@mitov.com. We will enable the editing as soon as we are happy with the overall Wiki site.
Package: IntelligenceLabPkg
Unit: ILNeuralNetwork
Inherits: TILNeuralNetworkTrain
Contents |
Syntax
Delphi:
type TILNeuralNetworkRPropTrain = class( TILNeuralNetworkTrain )
C++ Builder:
class TILNeuralNetworkRPropTrain : public TILNeuralNetworkTrain
Visual C++ (MFC):
class CTILNeuralNetworkRPropTrain : public CTILNeuralNetworkTrain
C# (.NET):
public ref class TILNeuralNetworkRPropTrain : Mitov.IntelligenceLab.NeuralNetworkTrain
Summary
Trains neural networks using RProp algorithm.
Description
This component is designed to train neural networks using RProp algorithm.
To use the component set the Neural Network to be trained in the NeuralNetwork property.
Diagram:
Properties
Published
- Weights - Specifies the training weights.
From TILNeuralNetworkTrain
Properties
Published
- NeuralNetwork - Specifies the Neural Network component to be trained.
- TerminationCriteria - Criteria for terminating the training.
- NormalizeTrainingWeights - Specifies if the weights should be normalized.
- ScaleInputs - Scales the inputs before the training.
- ScaleOutputs - Scales the outputs before the training.
Methods
Public
- function Train(AData : IILTrainingDataArray) : Integer - Trains the connected neural network.
- function Train(ATraingFeatures : ISLRealBuffer; AResposes : ISLRealBuffer) : Integer
- function Train(ATraingFeatures : ISLRealBuffer; AResposes : ISLRealBuffer; AWeights : Real) : Integer
- function Train(ATraingFeatures : ISLRealBufferArray; AResposes : ISLRealBufferArray) : Integer - Trains the connected neural network.
- function Train(ATraingFeatures : ISLRealBufferArray; AResposes : ISLRealBufferArray; AWeights : ISLRealBuffer) : Integer - Trains the connected neural network.
Pins
- InputPin - The training data input pin of the component.
- ProgressPin - The Training Progress Pin.
Events
- OnProgress - Training progress notification event.
- OnError - Occurs on training error.