select_vi: Feature Selection performed by Variable Importance algorithm...

In ModelOriented/forester: Quick and Simple Tools for Training and Testing of Tree-Based Models

Feature Selection performed by Variable Importance algorithm based on random forest

Description

Feature Selection performed by Variable Importance algorithm based on random forest

Usage

select_vi(data, y, nperm = 1, max_features = 10, verbose = FALSE)

Arguments

data	A data source, that is one of the major R formats: data.table, data.frame, matrix and so on.
y	A string that indicates a target column name.
nperm	An integer describing the number of permutations performed. By default set to 1.
max_features	A positive integer value describing the desired number of selected features. By default set to 10.
verbose	A logical value, if set to TRUE, provides all information about preprocessing process, if FALSE gives none.

Value

A list containing two objects:

• `data` A dataset with selected columns,

• `idx` The indexes of removed columns.

ModelOriented/forester documentation built on June 6, 2024, 7:29 a.m.