Split a dataset into training and a test sets.

This function prepares the cross-validation by splitting the data into num.folds training and test folds for num.resample times.

data.splitter(siamcat, num.folds = 2, num.resample = 1, stratify = TRUE,
  inseparable = NULL, verbose = 1)

Arguments

siamcat	object of class siamcat-class
num.folds	number of cross-validation folds (needs to be >=2), defaults to 2
num.resample	resampling rounds (values <= 1 deactivate resampling), defaults to 1
stratify	boolean, should the splits be stratified s. t. an equal proportion of classes are present in each fold?, defaults to TRUE
inseparable	column index or column name of metadata variable, defaults to NULL
verbose	control output: 0 for no output at all, 1 for only information about progress and success, 2 for normal level of information and 3 for full debug information, defaults to 1

Value

object of class siamcat-class