fpc: Flexible procedures for clustering
Various methods for clustering and cluster validation.
Fixed point clustering. Linear regression clustering.
Clustering by merging Gaussian mixture components. Symmetric
and asymmetric discriminant projections for visualisation of
the separation of groupings. Cluster validation statistics for
distance based clustering including corrected Rand index.
Cluster-wise cluster stability assessment. Methods for
estimation of the number of clusters: Calinski-Harabasz,
Tibshirani and Walther's prediction strength, Fang and Wang's
bootstrap stability. Gaussian/multinomial mixture fitting for
mixed continuous/categorical variables. Variable-wise
statistics for cluster interpretation. DBSCAN clustering.
Interface functions for many clustering methods implemented in
R, including estimating the number of clusters with kmeans, pam
and clara. Modality diagnosis for Gaussian mixtures. For an
overview see package?fpc.
||R (≥ 2.0), MASS, cluster, mclust, flexmix|
||trimcluster, prabclus, class, diptest, mvtnorm, robustbase, kernlab, tclust|
||Christian Hennig <c.hennig at ucl.ac.uk>|
||GPL-2 | GPL-3 [expanded from: GPL]|