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. Clusterwise cluster stability assessment. Methods for estimation of the number of clusters: Calinski-Harabasz, Tibshirani and Walther's prediction strength. Gaussian/multinomial mixture fitting for mixed continuous/categorical variables. Veriablewise 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. Note that the use of the package mclust (called by function prabclust) is protected by a special license, see http://www.stat.washington.edu/mclust/license.txt. For an overview see package?fpc.

Downloads:

Reverse dependencies: