Package: FPDclustering
Type: Package
Title: PD-Clustering and Factor PD-Clustering
Version: 1.2
Date: 2017-08-23
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: 2017-08-23 18:03:15 UTC; ctortora
Repository: CRAN
Date/Publication: 2017-08-23 18:08:58 UTC
Built: R 3.4.4; ; 2018-11-05 15:06:54 UTC; windows
