feature.selection.cv: Selection of features in cross-validation
In pavhrablis/benchmarkFS: What the Package Does (One Line, Title Case)

Description Usage Arguments Details Value Examples

Selection of features in cross-validation

1	feature.selection.cv(x, y, method, list.index.cross, params = list())

`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`	the name of the selection method for traits available in this library
`list.index.cross`	A `list` with indexes obtained in cross-validation
`params`	A `list` parameters required for this method of feature selection

Uses the methods of selection of features available in this library

A list with selected features for each iteration of cross-validation

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

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

list.selected.var <- feature.selection.cv(x = data,
                             y = class,
                             method = 'fs.utest',
                             list.index.cross = list.index.cross,
                             params = list(adjust = 'holm', alpha = 0.05))