Class ILNeuralNetwork.TILNeuralNetworkTrain

Revision as of 20:30, 10 June 2013 (view source) David Alm (Talk | contribs) (Automated Syncronization with Documentation) ← Older edit		Latest revision as of 00:32, 26 June 2013 (view source) David Alm (Talk | contribs) (Automated Syncronization with Documentation)
(5 intermediate revisions by one user not shown)
Line 26:		Line 26:
	=== C# (.NET): ===		=== C# (.NET): ===
	<code>		<code>
−	'''public ref class''' TILNeuralNetworkTrain : [[Class LPComponent.TLPComponent|Mitov.IntelligenceLab.Component]]	+	'''public ref class''' NeuralNetworkTrain : [[Class LPComponent.TLPComponent|Mitov.IntelligenceLab.Component]]
	</code>		</code>
	== Summary ==		== Summary ==

---

Latest revision as of 00:32, 26 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: TLPComponent

Contents 1 Syntax 1.1 Delphi: 1.2 C++ Builder: 1.3 Visual C++ (MFC): 1.4 C# (.NET): 2 Summary 3 Description 4 Properties 4.1 Published 5 Methods 5.1 Public 6 Pins 7 Events

Syntax

Delphi:

type TILNeuralNetworkTrain = class( TLPComponent )

C++ Builder:

class TILNeuralNetworkTrain : public TLPComponent

Visual C++ (MFC):

class CTILNeuralNetworkTrain : public CTLPComponent

C# (.NET):

public ref class NeuralNetworkTrain : Mitov.IntelligenceLab.Component

Summary

Basic abstract class for neural network training components.

Description

Defines basic abstract class for neural network training components.

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.