public virtual void Train(
	Network network,
	double[,] xData,
	double[,] yData
)

Public Overridable Sub Train ( 
	network As Network,
	xData As Double(,),
	yData As Double(,)
)

public:
virtual void Train(
	Network^ network, 
	array<double,2>^ xData, 
	array<double,2>^ yData
)

abstract Train : 
        network : Network * 
        xData : float[,] * 
        yData : float[,] -> unit 
override Train : 
        network : Network * 
        xData : float[,] * 
        yData : float[,] -> unit 

Parameters

network

Type: Imsl.DataMining.NeuralNetwork
The Network to be trained.

xData

Type: SystemDouble
A double matrix specifying the input training patterns. The number of columns in xData must equal the number of Nodes in the InputLayer.

yData

Type: SystemDouble
A double containing the output training patterns. The number of columns in yData must equal the number of Perceptrons in the OutputLayer.

Implements

Each row of xData and yData contains a training pattern. These number of rows in two arrays must be equal.

Reference