transform_features_iterative

Once <code>decide_variable_type_iterative</code> has chosen which
 variables to add (and how), we can build a final data frame from those
 decisions.

internal

Implements 'SplitWise', a hybrid regression approach that transforms
numeric variables into either single-split (0/1) dummy variables or retains
them as continuous predictors. The transformation is followed by stepwise
selection to identify the most relevant variables. The default 'iterative'
mode adaptively explores partial synergies among variables to enhance model
performance, while an alternative 'univariate' mode applies simpler
transformations independently to each predictor. For details, see Kurbucz et al. (2025) <doi:10.48550/arXiv.2505.15423>.

Marcell T. Kurbucz

SplitWise

Hybrid Stepwise Regression with Single-Split Dummy Encoding

Nikolaos Tzivanakis

Nilufer Sari Aslam

Adam M. Sykulski

transform_features_iterative function

<dl><dt>X</dt>
<dd>Original predictor data frame.</dd>
<dt>decisions</dt>
<dd>Output of <code>decide_variable_type_iterative</code>.</dd></dl>

Arguments

Transform Features (Iterative Logic) — transform_features_iterative

<dl>

<dt>X</dt>
<dd>Original predictor data frame.</dd>


<dt>decisions</dt>
<dd>Output of <code>decide_variable_type_iterative</code>.</dd>

</dl>

transform_features_iterative: Transform Features (Iterative Logic)

Description

Usage

Value

Arguments