resolve_positive_class

Determines the positive class respecting event_class settings from fastml().
This ensures consistency across all explainer functions.

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

resolve_positive_class function

<dl><dt>prep</dt>
<dd>A list from fastml_prepare_explainer_inputs containing:
positive_class, event_class, label_levels</dd>
<dt>y_levels</dt>
<dd>Character vector of actual levels from the target variable</dd></dl>

Arguments

Resolve the positive class for binary classification — resolve_positive_class

<dl>

<dt>prep</dt>
<dd>A list from fastml_prepare_explainer_inputs containing:
positive_class, event_class, label_levels</dd>


<dt>y_levels</dt>
<dd>Character vector of actual levels from the target variable</dd>

</dl>

resolve_positive_class: Resolve the positive class for binary classification

Description

Usage

Value

Arguments