Computes error statistics.

Namespace: Imsl.DataMining.Neural
Assembly: ImslCS (in ImslCS.dll) Version: 6.5.0.0

Syntax

C#
public virtual double[] ComputeStatistics(
	double[,] xData,
	double[,] yData
)
Visual Basic (Declaration)
Public Overridable Function ComputeStatistics ( _
	xData As Double(,), _
	yData As Double(,) _
) As Double()
Visual C++
public:
virtual array<double>^ ComputeStatistics(
	array<double,2>^ xData, 
	array<double,2>^ yData
)

Parameters

xData
Type: array< System..::.Double ,2>[,](,)[,]
A double matrix containing the input values.
yData
Type: array< System..::.Double ,2>[,](,)[,]
A double array containing the observed values.

Return Value

A double array containing the above described statistics.

Remarks

This is a static method that can be used to compute the statistics regardless of the training class used to train the Network.

Computes statistics related to the error. In this table, the observed values are y_i. The forecasted values are \hat{y}_i. The mean observed value is \bar{y} = \sum_i y_i / NC, where N is the number of observations and C is the number of classes per observation.

IndexNameFormula
0SSE\frac{1}{2} \sum_i\left(y_i-\hat{y}_i\right)^2
1RMS\frac{\sum_i \left(y_i-\hat{y}_i\right)^2}{\sum_i\left(y_i-\bar{y}_i\right)}
2Laplacian\sum_i \left|y_i-\hat{y}_i\right|
3Scaled Laplacian \frac{\sum_i \left|y_i-\hat{y}_i\right|}{\sum_i\left|y_i-\bar{y}_i \right|}
4Max residual \max_i\left|y_i-\hat{y}_i\right|

See Also