combo_filter

Filter combining univariate (t-test or anova) filtering and reliefF filtering
in equal measure.

Implements nested k*l-fold cross-validation for lasso and elastic-net regularised linear models via the 'glmnet' package and other machine learning models via the 'caret' package <doi:10.1093/bioadv/vbad048>. Cross-validation of 'glmnet' alpha mixing parameter and embedded fast filter functions for feature selection are provided. Described as double cross-validation by Stone (1977) <doi:10.1111/j.2517-6161.1977.tb01603.x>. Also implemented is a method using outer CV to measure unbiased model performance metrics when fitting Bayesian linear and logistic regression shrinkage models using the horseshoe prior over parameters to encourage a sparse model as described by Piironen & Vehtari (2017) <doi:10.1214/17-EJS1337SI>.

Myles Lewis

nestedcv

Nested Cross-Validation with 'glmnet' and 'caret'

Athina Spiliopoulou

Cankut Cubuk

David Rios Santini

Katriona Goldmann

Ryan C. Thompson

combo_filter function

<dl><dt>y</dt>
<dd>Response vector</dd>
<dt>x</dt>
<dd>Matrix or dataframe of predictors</dd>
<dt>nfilter</dt>
<dd>Number of predictors to return, using 1/2 from <code>ttest_filter</code>
or <code>anova_filter</code> and 1/2 from <code>relieff_filter</code>. Since <code>unique</code> is applied,
the final number returned may be less than <code>nfilter</code>.</dd>
<dt>type</dt>
<dd>Type of vector returned. Default "index" returns indices,
"names" returns predictor names, "full" returns full output.</dd>
<dt>...</dt>
<dd>Optional arguments passed via relieff_filter to
CORElearn::attrEval</dd></dl>

Arguments

Combo filter — combo_filter

<dl>

<dt>y</dt>
<dd>Response vector</dd>


<dt>x</dt>
<dd>Matrix or dataframe of predictors</dd>


<dt>nfilter</dt>
<dd>Number of predictors to return, using 1/2 from <code>ttest_filter</code>
or <code>anova_filter</code> and 1/2 from <code>relieff_filter</code>. Since <code>unique</code> is applied,
the final number returned may be less than <code>nfilter</code>.</dd>


<dt>type</dt>
<dd>Type of vector returned. Default "index" returns indices,
"names" returns predictor names, "full" returns full output.</dd>


<dt>...</dt>
<dd>Optional arguments passed via relieff_filter to
CORElearn::attrEval</dd>

</dl>

combo_filter: Combo filter

Description

Usage

Value

Arguments