C# 클래스 NNX.Core.MultilayerPerceptron

Multilayer perceptron with the following features: * Hidden layer activation functions: tahn * Output layer activation function: softmax * Gradient calculation assumes optimization for min cross-entropy error.

상속: INeuralNetwork

파일 보기 프로젝트 열기: ikhramts/NNX

공개 메소드들

메소드	설명
CalculateGradients ( double inputs, double targets ) : double[][]	Calculates gradients of the error function (cross-entropy) with respect to weights.
FeedForward ( double inputs ) : FeedForwardResult	Activation functions: tanh for hidden nodes, softmax for output nodes.
MultilayerPerceptron ( int numInputs, int numOutputs, IList hiddenLayerSizes ) : System

메소드 상세

CalculateGradients() 공개 메소드

Calculates gradients of the error function (cross-entropy) with respect to weights.

public CalculateGradients ( double inputs, double targets ) : double[][]
inputs	double
targets	double
리턴	double[][]

FeedForward() 공개 메소드

Activation functions: tanh for hidden nodes, softmax for output nodes.

public FeedForward ( double inputs ) : FeedForwardResult
inputs	double
리턴	FeedForwardResult

MultilayerPerceptron() 공개 메소드

public MultilayerPerceptron ( int numInputs, int numOutputs, IList hiddenLayerSizes ) : System
numInputs	int
numOutputs	int
hiddenLayerSizes	IList
리턴	System