vi_predictors

<p>Predictor names in data frame 'vi'</p>

datasets

System for seamless management of multicollinearity in data frames
with numeric and/or categorical variables for statistical analysis and
machine learning modeling. The package combines bivariate correlation
(Pearson, Spearman, and Cramer's V) with variance inflation factor analysis,
target encoding to transform categorical variables into numeric (Micci-Barreca, D. 2001
<DOI:10.1145/507533.507538>), and a flexible
feature prioritization method, to deliver a comprehensive
multicollinearity management tool covering a wide range of use cases.

Blas M. Benito

collinear

Seamless Multicollinearity Management

vi_predictors function

<p>Character vector with predictor names.</p>

vi_predictors: Predictor names in data frame 'vi'

Description

Usage

Arguments

Format

See Also