availableMethods

Returns a character vector of algorithm names available for classification,
regression or survival tasks.

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

availableMethods function

<dl><dt>type</dt>
<dd>A character string specifying the type of task. Must be one of
<code>"classification"</code>, <code>"regression"</code>, or <code>"survival"</code>. Defaults to
<code>c("classification", "regression", "survival")</code> and uses
<code><a href="/link/match.arg?package=fastml&version=0.7.7" data-mini-rdoc="fastml::match.arg">match.arg</a></code> to select one.</dd>
<dt>...</dt>
<dd>Additional arguments (currently not used).</dd></dl>

Arguments

Get Available Methods — availableMethods

<dl>

<dt>type</dt>
<dd>A character string specifying the type of task. Must be one of
<code>"classification"</code>, <code>"regression"</code>, or <code>"survival"</code>. Defaults to
<code>c("classification", "regression", "survival")</code> and uses
<code><a href='https://rdrr.io/r/base/match.arg.html'>match.arg</a></code> to select one.</dd>


<dt>...</dt>
<dd>Additional arguments (currently not used).</dd>

</dl>

availableMethods: Get Available Methods

Description

Usage

Value

Arguments

Details