public virtual double[] ComputeStatistics(
	double[,] xData,
	int[] yData
)

Public Overridable Function ComputeStatistics ( 
	xData As Double(,),
	yData As Integer()
) As Double()

public:
virtual array<double>^ ComputeStatistics(
	array<double,2>^ xData, 
	array<int>^ yData
)

abstract ComputeStatistics : 
        xData : float[,] * 
        yData : int[] -> float[] 
override ComputeStatistics : 
        xData : float[,] * 
        yData : int[] -> float[] 

Parameters

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: SystemInt32
An int array containing the output classification patterns. The values in yData must be 0 or 1.

Return Value

The first element returned is the binary cross-entropy error; the second is the classification error rate. The classification error rate is calculated by comparing the estimated classification probabilities to the target classifications. If the estimated probability for the target class is less than 0.5, then this is tallied as a classification error.

Reference