getBER

Get Balanced Error Rate (BER) in classification.

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

getBER function

<dl><dt>actual</dt>
<dd>Vector of actual classifications of samples</dd>
<dt>predicted</dt>
<dd>Vector of predicted classifications of samples</dd>
<dt>weigh_added</dt>
<dd>To add a weighing matrix when it is classification</dd>
<dt>weighing_matrix</dt>
<dd>The matrix used to get a misclassification score</dd></dl>

Arguments

Get BER — getBER

<dl>

<dt>actual</dt>
<dd>Vector of actual classifications of samples</dd>


<dt>predicted</dt>
<dd>Vector of predicted classifications of samples</dd>


<dt>weigh_added</dt>
<dd>To add a weighing matrix when it is classification</dd>


<dt>weighing_matrix</dt>
<dd>The matrix used to get a misclassification score</dd>

</dl>

getBER: Get BER

Description

Usage

Value

Arguments

Examples