Partitioning clustering algorithms divide data sets into k subsets or partitions socalled clusters. They require some initialization procedures for starting to partition the data sets. Initialization of cluster prototypes is one of such kind of procedures for most of the partitioning algorithms. Cluster prototypes are the data elements, i.e. centroids or medoids, representing the clusters in a data set. In order to initialize cluster prototypes, the package 'inaparc' contains a set of the functions that are the implementations of several linear timecomplexity and loglinear timecomplexity methods in addition to some novel techniques. Initialization of fuzzy membership degrees matrices is another important task for starting the probabilistic and possibilistic partitioning algorithms. In order to initialize membership degrees matrices required by these algorithms, a number of functions based on some traditional and novel initialization techniques are also available in the package 'inaparc'.
Package details 


Author  Zeynel Cebeci [aut, cre], Cagatay Cebeci [aut] 
Date of publication  20171104 23:25:17 UTC 
Maintainer  Zeynel Cebeci <[email protected]> 
License  GPL (>= 2) 
Version  0.2.0 
Package repository  View on CRAN 
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