splitForTrainingAndTest: Function to split data into training and test set

In RSNNS: Neural Networks using the Stuttgart Neural Network Simulator (SNNS)

Function to split data into training and test set

Description

Split the input and target values to a training and a test set. Test set is taken from the end of the data. If the data is to be shuffled, this should be done before calling this function.

Usage

splitForTrainingAndTest(x, y, ratio = 0.15)

Arguments

x	inputs
y	targets
ratio	ratio of training and test sets (default: 15% of the data is used for testing)

Value

a named list with the following elements:

inputsTrain	a matrix containing the training inputs
targetsTrain	a matrix containing the training targets
inputsTest	a matrix containing the test inputs
targetsTest	a matrix containing the test targets

Examples

data(iris)
#shuffle the vector
iris <- iris[sample(1:nrow(iris),length(1:nrow(iris))),1:ncol(iris)]

irisValues <- iris[,1:4]
irisTargets <- decodeClassLabels(iris[,5])

splitForTrainingAndTest(irisValues, irisTargets, ratio=0.15)

RSNNS documentation built on May 29, 2024, 4:37 a.m.