warn_default_override

Issues a warning if fastml defaults differ from parsnip defaults and
the warning hasn't been shown yet in this session.

Provides a guarded resampling workflow for training and evaluating machine-learning models.
When the guarded resampling path is used, preprocessing and model fitting are re-estimated within
each resampling split to reduce leakage risk. Supports multiple resampling schemes, integrates
with established engines in the 'tidymodels' ecosystem, and aims to improve evaluation reliability by
coordinating preprocessing, fitting, and evaluation within supported workflows. Offers a lightweight
AutoML-style workflow by automating model training, resampling, and tuning across multiple algorithms,
while keeping evaluation design explicit and user-controlled.

Selcuk Korkmaz

fastml

Guarded Resampling Workflows for Safe and Automated Machine
Learning in R

Dincer Goksuluk

Eda Karaismailoglu

warn_default_override function

<dl><dt>algo</dt>
<dd>Algorithm name.</dd>
<dt>task</dt>
<dd>Task type.</dd>
<dt>fastml_engine</dt>
<dd>fastml's default engine for this algorithm.</dd>
<dt>fastml_params</dt>
<dd>fastml's default parameters (optional).</dd>
<dt>verbose</dt>
<dd>If TRUE, always show the message (as a message, not warning).</dd>
<dt>warn_once</dt>
<dd>If TRUE (default), only warn once per algorithm per session.</dd></dl>

Arguments

Warn About Default Overrides — warn_default_override

<dl>

<dt>algo</dt>
<dd>Algorithm name.</dd>


<dt>task</dt>
<dd>Task type.</dd>


<dt>fastml_engine</dt>
<dd>fastml's default engine for this algorithm.</dd>


<dt>fastml_params</dt>
<dd>fastml's default parameters (optional).</dd>


<dt>verbose</dt>
<dd>If TRUE, always show the message (as a message, not warning).</dd>


<dt>warn_once</dt>
<dd>If TRUE (default), only warn once per algorithm per session.</dd>

</dl>

warn_default_override: Warn About Default Overrides

Description

Usage

Value

Arguments