evaluation
, generated
with scheme = "observationwise"
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 caseTRUE
.data.frame
containing the indices
of consistenly misclassfied observations and
the corresponding performance measure.Slawski, M. Daumer, M. Boulesteix, A.-L. (2008) CMA - A comprehensive Bioconductor package for supervised classification with high dimensional data. BMC Bioinformatics 9: 439
evaluation