pm_clustering Module Reference

This module contains procedures and routines for the computing the Kmeans clustering of a given set of data. More...

Data Types
interface	setCenter
	Compute and return the centers of the clusters corresponding to the input sample, cluster membership IDs, and sample distances-squared from their corresponding cluster centers. More...
interface	setKmeans
	Compute and return an iteratively-refined set of cluster centers given the input sample using the k-means approach. More...
interface	setKmeansPP
	Compute and return an asymptotically optimal set of cluster centers for the input sample, cluster membership IDs, and sample distances-squared from their corresponding cluster centers. More...
interface	setMember
	Compute and return the memberships and minimum distances of a set of input points with respect to the an input set of cluster centers. More...

Variables
character(*, SK), parameter	MODULE_NAME = "@pm_clustering"

Detailed Description

This module contains procedures and routines for the computing the Kmeans clustering of a given set of data.

See also

Test:

test_pm_clustering

Final Remarks ⛓

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Copyright

Computational Data Science Lab

Author:

Amir Shahmoradi, April 03, 2017, 2:16 PM, Institute for Computational Engineering and Sciences (ICES), University of Texas at Austin

Variable Documentation

MODULE_NAME

character(*, SK), parameter pm_clustering::MODULE_NAME = "@pm_clustering"

Definition at line 42 of file pm_clustering.F90.