allMethods

Machine learning model table for mlComb()
Includes machine learning models used for the mlComb function

datasets

A system for combining two diagnostic tests using various approaches
that include statistical and machine-learning-based methodologies.
These approaches are divided into four groups: linear combination
methods, non-linear combination methods, mathematical operators,
and machine learning algorithms. See
the <https://biotools.erciyes.edu.tr/dtComb/> website
for more information, documentation, and examples.

Gokmen Zararsiz

dtComb

Statistical Combination of Diagnostic Tests

Serra Ilayda Yerlitas

Serra Bersan Gengec

Necla Kochan

Gozde Erturk Zararsiz

Selcuk Korkmaz

allMethods function

A data frame with 113 rows and 2 variables:<dl>
<dt>Method</dt>
<dd>Valid name for the function</dd><dt>Model</dt>
<dd>Model name</dd>
</dl>

Format

Machine learning model table for mlComb()
Includes machine learning models used for the mlComb function — allMethods

A data frame with 113 rows and 2 variables:<dl>
<dt>Method</dt>
<dd>Valid name for the function</dd>

<dt>Model</dt>
<dd>Model name</dd>


</dl>

allMethods: Machine learning model table for mlComb() Includes machine learning models used for the mlComb function

Description

Usage

Arguments

Format

Examples