Package: FPDclustering
Type: Package
Title: PD-Clustering and Factor PD-Clustering
Version: 1.0
Date: 2014-12-16
Author: Cristina Tortora and Paul D. McNicholas
Maintainer: Cristina Tortora <grikris1@gmail.com>
Description: Probabilistic distance clustering (PD-clustering) is an iterative, distribution free, probabilistic clustering method. PD-clustering assigns units to a cluster according to their probability of membership, under the constraint that the product of the probability and the distance of each point to any cluster centre is a constant. PD-clustering is a flexible method that can be used with non-spherical clusters, outliers, or noisy data. Facto PD-clustering (FPDC) is a recently proposed factor clustering method that involves a linear transformation of variables and a cluster optimizing the PD-clustering criterion. It allows clustering of high dimensional data sets.
Depends: ThreeWay
License: GPL (>= 2)
Packaged: 2014-12-16 18:46:17 UTC; ctortora
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2014-12-17 01:54:43
