wmc {CMA} | R Documentation

## Tuning / Selection bias correction based on matrix of subsampling fold errors

### Description

Perform tuning / selection bias correction for a matrix of subsampling fold errors.

### Usage

    wmc(mcr.m,n.tr,n.ts,shrinkage=F)

### Arguments

`mcr.m` | A matrix of resampling fold errors. Columns correspond the the fold errors of a single classifier.
`n.tr` | Number of observations in the resampling training sets.
`n.ts` | Number of observations in the resampling test sets.
`shrinkage` | A logical value indicating whether shrinkage (WMCS) shall be applied.

### Details

The algorithm tries to avoid the additional computational costs of a nested cross validation by estimating the corrected misclassification rate of the best classifier by a weighted mean of all classifiers included in the subsampling approach.

### Value

A list containing the corrected misclassification rate, the index of the best method and a logical value indicating whether shrinkage has been applied.

### Author(s)

Christoph Bernau bernau@ibe.med.uni-muenchen.de

Anne-Laure Boulesteix boulesteix@ibe.med.uni-muenchen.de

### References

Bernau Ch., Augustin, Th. and Boulesteix, A.-L. (2011): Correcting the optimally selected resampling-based error rate: A smooth analytical alternative to nested cross-validation. Department of Statistics: Technical Reports, Nr. 105.

### See Also

`weighted.mcr`,`classification`,`GeneSelection`, `tune`, `evaluation`,

[Package CMA version 1.38.0 Index]