nearZeroVar

Adapted and stripped down from mixOmics v 5.2.0 (https://cran.r-project.org/web/packages/mixOmics/).

Predictive multivariate modelling for metabolomics.
Types: Classification and regression.
Methods: Partial Least Squares, Random Forest ans Elastic Net
Data structures: Paired and unpaired Validation: repeated double cross-validation (Westerhuis et al. (2008)<doi:10.1007/s11306-007-0099-6>, Filzmoser et al. (2009)<doi:10.1002/cem.1225>)
Variable selection: Performed internally, through tuning in the inner cross-validation loop.

Yingxiao Yan

MUVR2

Multivariate Methods with Unbiased Variable Selection

Carl Brunius

nearZeroVar function

<dl><dt>x</dt>
<dd>a numeric vector or matrix, or a data frame with all numeric data.</dd>
<dt>freqCut</dt>
<dd>the cutoff for the ratio of the most common value to the second most common value.</dd>
<dt>uniqueCut</dt>
<dd>the cutoff for the percentage of distinct values out of the number of total samples.</dd></dl>

Arguments

Identify variables with near zero variance — nearZeroVar

<dl>

<dt>x</dt>
<dd>a numeric vector or matrix, or a data frame with all numeric data.</dd>


<dt>freqCut</dt>
<dd>the cutoff for the ratio of the most common value to the second most common value.</dd>


<dt>uniqueCut</dt>
<dd>the cutoff for the percentage of distinct values out of the number of total samples.</dd>

</dl>

nearZeroVar: Identify variables with near zero variance

Description

Usage

Value

Arguments

Examples