Probabilistic distance clustering (PDclustering) is an iterative, distribution free, probabilistic clustering method. PDclustering 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. PDclustering is a flexible method that can be used with nonspherical clusters, outliers, or noisy data. Facto PDclustering (FPDC) is a recently proposed factor clustering method that involves a linear transformation of variables and a cluster optimizing the PDclustering criterion. It works on high dimensional datasets.
Package details 


Author  Cristina Tortora and Paul D. McNicholas 
Date of publication  20170823 18:08:58 UTC 
Maintainer  Cristina Tortora <[email protected]> 
License  GPL (>= 2) 
Version  1.2 
Package repository  View on CRAN 
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