MultivariateRandomForest (version 1.1)

CrossValidation: Matrix of Input and Output of Cross validation

Description

Generates Cross validated Input Matices and Output Vectors, where number of fold in cross validation is user defined

Usage

CrossValidation(X, Y, F)

Arguments

X

M x N Input matrix, M is the number of samples and N is the number of features

Y

output Response as column vector

F

Number of Fold in cross validation

Value

List with the following components:

TrainingData

List of matices with matrix containing Cross Validates Training Data, where number of list equal to user defined cross validation

TestingData

List of matices with matrix containing Cross Validates Testing Data, where number of list equal to user defined cross validation

OutputTrain

List of matices with matrix containing Cross Validates Training Response Data, where number of list equal to user defined cross validation

OutputTest

List of matices with matrix containing Cross Validates Testing Response Data, where number of list equal to user defined cross validation

FoldedIndex

Index of Different Fold