Data Mining Algorithms In R/Packages/CCMtools/Percent.bad.and.false.classif.per.cluster
Description
editThis function computes the percentage of bad and false classification of a sequence of clusters (new.cl) according to a reference sequence (cl).
Usage
editPercent.bad.and.false.classif.per.cluster(cl, new.cl)
Arguments
edit- cl Reference sequence of clusters.
- new.cl Sequence of clusters to be compared to the reference sequence.
Value
editReturns a list containing the following elements:
- tot Global percentage of bad classification
- BadPerCluster Percentage of bad classification per cluster
- FalsePerCluster Percentage of false classification per cluster
- mat.att Global matrix of attribution (row = cl, colomn = new.cl)
Author
editM. Vrac (mathieu.vrac@lsce.ipsl.fr))