check_data_variability

Validates that the response variable and all predictor variables have more
than one unique value.

internal

Implements Interpretable Boosted Linear Models (IBLMs). These combine a conventional generalized linear model (GLM) with a machine learning component, such as XGBoost. The package also provides tools within for explaining and analyzing these models. For more details see Gawlowski and Wang (2025) <https://ifoa-adswp.github.io/IBLM/reference/figures/iblm_paper.pdf>.

Karol Gawlowski

IBLM

Interpretable Boosted Linear Models

check_data_variability function

<dl><dt>data</dt>
<dd>A data frame containing the variables to check.</dd>
<dt>response_var</dt>
<dd>Character string naming the response variable in `data`.</dd></dl>

Arguments

Check Data Variability for Modeling — check_data_variability

<dl>

<dt>data</dt>
<dd>A data frame containing the variables to check.</dd>


<dt>response_var</dt>
<dd>Character string naming the response variable in `data`.</dd>

</dl>

check_data_variability: Check Data Variability for Modeling

Description

Usage

Value

Arguments