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)) See Also ../learn.and.project.clusters/