RelevantVariables.MDFS

Find indices of relevant variables from MDFS

Functions for MultiDimensional Feature Selection (MDFS):
calculating multidimensional information gains, scoring variables,
finding important variables, plotting selection results.
This package includes an optional CUDA implementation that speeds up
information gain calculation using NVIDIA GPGPUs.
R. Piliszek et al. (2019) <doi:10.32614/RJ-2019-019>.

Radosław Piliszek

MDFS

MultiDimensional Feature Selection

Krzysztof Mnich

Paweł Tabaszewski

Szymon Migacz

Andrzej Sułecki

RelevantVariables.MDFS function

<dl><dt>fs</dt>
<dd>an MDFS object</dd>
<dt>level</dt>
<dd>statistical significance level</dd>
<dt>p.adjust.method</dt>
<dd>method as accepted by <code><a href="/link/p.adjust?package=MDFS&version=1.5.5" data-mini-rdoc="MDFS::p.adjust">p.adjust</a></code> (<code>"BY"</code> is recommended for FDR, see Details)</dd>
<dt>...</dt>
<dd>ignored</dd></dl>

Arguments

Find indices of relevant variables from MDFS — RelevantVariables.MDFS

<dl>

<dt>fs</dt>
<dd>an MDFS object</dd>


<dt>level</dt>
<dd>statistical significance level</dd>


<dt>p.adjust.method</dt>
<dd>method as accepted by <code><a href='https://rdrr.io/r/stats/p.adjust.html'>p.adjust</a></code> (<code>"BY"</code> is recommended for FDR, see Details)</dd>


<dt>...</dt>
<dd>ignored</dd>

</dl>

RelevantVariables.MDFS: Find indices of relevant variables from MDFS

Description

Usage

Value

Arguments

Details