wmc: 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.
Value
of the best method and a logical value indicating whether
shrinkage has been 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.
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.