evaluateClusters: Validating A Clusteranalysis

In VZoche-Golob/ClusterTools: Convenience Tools For Clusteranalyses

Validating A Clusteranalysis

Description

Called by compareClustering().

Usage

evaluateClusters(xList)

Arguments

xList

a list with the following elements: dm a string describing a distance measure (currently, only "euclidean", "maximum", "manhattan", "canberra", "binary" or "minkowski" are allowed) method a string naming a clustering method (currently, the following are allowed: "ward.D", "ward.D2", "single", "complete" , "average", "mcquitty", "median", "centroid" (use stats::hclust) "diana" (uses cluster::diana) "kmeans" (uses cluster::pam) ) k the maximum number of clusters distData a distance matrix

Value

a tibble::tibble with one row per number of clusters from 2 to k and the columns:

distance

= dm

method

= method

nCluster

= k

totalAvgSilWidth

overall average silhoutte width (cluster::summary.silhouette$avg.width)

minClustAvgSilWidth

minimal average cluster silhoutte width (cluster::summary.silhouette$clus.avg.widths)

minSilWidth

minimal silhoutte width (cluster::summary.silhouette$si.summary$`Min.`)

pPosSilWidths

percentage of positive silhoutte widths

minClustJacMean

minimal cluster bootstrap mean of Jaccard's index (fpc::clusterboot$bootmean)

pClustJacOver06

percentage of cluster bootstrap means of Jaccard's index above 0.6

separationIndex

fpc::cluster.stats$sindex

avgDistWithin

fpc::cluster.stats$average.within

withinVsBetween

fpc::cluster.stats$wb.ratio

VZoche-Golob/ClusterTools documentation built on April 3, 2022, 6:52 a.m.