Data Mining Algorithms In R/Packages/CCMtools/Percent.bad.and.false.classif.per.cluster

Description
This function computes the percentage of bad and false classification of a sequence of clusters (new.cl) according to a reference sequence (cl).

Usage
Percent.bad.and.false.classif.per.cluster(cl, new.cl)

Arguments

 * cl  Reference sequence of clusters.


 * new.cl  Sequence of clusters to be compared to the reference sequence.

Value
Returns 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
M. Vrac (mathieu.vrac@lsce.ipsl.fr))