Package: FPDclustering
Type: Package
Title: PD-Clustering and Factor PD-Clustering
Version: 1.1
Date: 2016-05-12
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 works on high dimensional datasets.
Depends: ThreeWay
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2016-05-17 20:11:58 UTC; ctortora
Repository: CRAN
Date/Publication: 2016-05-18 01:23:36
Built: R 3.2.5; ; 2016-11-02 14:21:09 UTC; windows
