public virtual void Train(
	ITrainer trainer,
	double[,] xData,
	int[] yData
)

Public Overridable Sub Train ( 
	trainer As ITrainer,
	xData As Double(,),
	yData As Integer()
)

public:
virtual void Train(
	ITrainer^ trainer, 
	array<double,2>^ xData, 
	array<int>^ yData
)

abstract Train : 
        trainer : ITrainer * 
        xData : float[,] * 
        yData : int[] -> unit 
override Train : 
        trainer : ITrainer * 
        xData : float[,] * 
        yData : int[] -> unit 

Parameters

trainer

Type: Imsl.DataMining.NeuralITrainer
A Trainer object, which is used to train the network. The error function in any QuasiNewton trainer included in trainer should be set to the error function from this class using the Error method.

xData

Type: SystemDouble
A double matrix containing the input training patterns. The number of columns in xData must equal the number of nodes in the input layer. Each row of xData contains a training pattern.

yData

Type: SystemInt32
An int array containing the output classification patterns. These values must be in the range of one to the number of output perceptrons in the network.

Reference