compare_defaults

Compares the default engine and parameter choices between fastml and parsnip
for a given algorithm.

internal

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

compare_defaults function

<dl><dt>algo</dt>
<dd>Character string specifying the algorithm name.</dd>
<dt>task</dt>
<dd>Character string specifying the task type.</dd>
<dt>fastml_engine</dt>
<dd>Character string of the fastml default engine.</dd>
<dt>fastml_params</dt>
<dd>List of fastml default parameters.</dd></dl>

Arguments

Compare fastml and parsnip defaults — compare_defaults

<dl>

<dt>algo</dt>
<dd>Character string specifying the algorithm name.</dd>


<dt>task</dt>
<dd>Character string specifying the task type.</dd>


<dt>fastml_engine</dt>
<dd>Character string of the fastml default engine.</dd>


<dt>fastml_params</dt>
<dd>List of fastml default parameters.</dd>

</dl>

compare_defaults: Compare fastml and parsnip defaults

Description

Usage

Value

Arguments