cross.val: Cross-validation
In pavhrablis/benchmarkFS: What the Package Does (One Line, Title Case)

Description Usage Arguments Details Value Examples

Cross-validation

1	cross.val(x, y, method, params.cv = list(niter = 10, k = 3, test.size = 0.3))

`x`	input data where columns are variables and rows are observations (all numeric)
`y`	decision variable as a boolean vector of length equal to number of observations
`method`	cross-validation method `kfoldcv` for cross-validation `k-fold` or `rsampling` for `random sampling`
`params`	A `list` with the following fields: `niter` – the number of validation repetitions `k` – the number of groups that a given data sample is to be split into `test.size` – testing set size for random sampling validation

creates a list with division of observational indices of the dataframe of observational indices into training and test subsamples of a given number of iterations Implements two methods : cross-validation k-fold and random sampling

A list with lindices divided into train and test subsamples niter repetitions.

decisions <- data$class
data$class <- NULL

list.index.cross <- cross.val(x = data, y = decisions, method = 'kfoldcv', params.cv = list(niter = 10, k = 3))