fastml_guard_detect_full_analysis

Internal helpers that enforce the Guarded Resampling Principle by
fitting preprocessing pipelines independently within each resampling
split. These functions are not exported.

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

fastml_guard_detect_full_analysis function

<dl><dt>split</dt>
<dd>An `rsample` split object representing a single resample.</dd>
<dt>total_rows</dt>
<dd>Integer; total number of rows in the original dataset.</dd></dl>

Arguments

Guarded Resampling Utilities — fastml_guard_detect_full_analysis

<dl>

<dt>split</dt>
<dd>An `rsample` split object representing a single resample.</dd>


<dt>total_rows</dt>
<dd>Integer; total number of rows in the original dataset.</dd>

</dl>

fastml_guard_detect_full_analysis: Guarded Resampling Utilities

Description

Usage

Arguments