[SerializableAttribute]
public class PLS2CrossValidation : ICloneable

<SerializableAttribute> _
Public Class PLS2CrossValidation _
	Implements ICloneable

[SerializableAttribute]
public ref class PLS2CrossValidation : ICloneable

Evaluation consists of dividing the data into two subsets - a training subset and a testing subset. A PLS calculation is performed on the the training subset and the resulting model is used to predict the values of the dependent variables in the testing set. The mean square error between the actual and predicted dependent values is then calculated. Usually, the data is divided up into several training and testing subsets and calculations are done on each of these. In this case the average mean square error over each PLS calculation is reported (the individual mean square errors are available as well).

The subsets to use in the cross validation are specifed by providing an implementation of the ICrossValidationSubsets interface. Classes that implement this interface generate training and testing subsets from PLS data.

System..::.Object
  CenterSpace.NMath.Stats..::.PLS2CrossValidation