get_default_differences

Returns a summary of all differences between fastml and parsnip defaults
for the specified algorithms.

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

get_default_differences function

<dl><dt>algorithms</dt>
<dd>Character vector of algorithm names.</dd>
<dt>task</dt>
<dd>Task type ("classification", "regression", or "survival").</dd></dl>

Arguments

Get All Default Differences Summary — get_default_differences

<dl>

<dt>algorithms</dt>
<dd>Character vector of algorithm names.</dd>


<dt>task</dt>
<dd>Task type ("classification", "regression", or "survival").</dd>

</dl>

get_default_differences: Get All Default Differences Summary

Description

Usage

Value

Arguments