obsinfo {CMA}R Documentation

Classifiability of observations

Description

Some observations are harder to classify than others. It is frequently of interest to know which observations are consistenly misclassified; these are candiates for outliers or wrong class labels.

Arguments

object

An object of class evaluation, generated with scheme = "observationwise"

threshold

threshold value of (observation-wise) performance measure, s. evaluation that has to be exceeded in order to speak of consistent misclassification. If measure = "average probability", then values below threshold are regarded as consistent misclassification. Note that the default values 1 is not sensible in that case

show

Should the information be printed ? Default is TRUE.

Details

As not all observation must have been classified at least once, observations not classified at all are also shown.

Value

A list with two components

misclassification

A data.frame containing the indices of consistenly misclassfied observations and the corresponding performance measure.

notclassified

The indices of those observations not classfied at all, s. details.

Author(s)

Martin Slawski ms@cs.uni-sb.de

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

References

Slawski, M. Daumer, M. Boulesteix, A.-L. (2008) CMA - A comprehensive Bioconductor package for supervised classification with high dimensional data. BMC Bioinformatics 9: 439

See Also

evaluation


[Package CMA version 1.48.0 Index]