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Analysis of user-weighted pi rough k-means
Peters, Georg Lingras, Pawan
Peters, Georg
Lingras, Pawan
Author
Abstract
Since its introduction by Lingras and West a decade ago, rough k-means has gained increasing attention in academia as well as in practice. A recently introduced extension, π rough k-means, eliminates need for the weight parameter in rough k-means applying probabilities derived from Laplace’s Principle of Indifference. However, the proposal in its more general form makes it possible to optionally integrate user-defined weights for parameter tuning using techniques such as evolutionary computing. In this paper, we study the properties of this general user-weighted π k-means through extensive experiments.
Keywords
Rough k-Means, User-Defined Weights, Soft Clustering
Date
2014
Type
Conference item
Journal
Book
Volume
Issue
Page Range
547-556
Article Number
ACU Department
School of Arts and Humanities
Faculty of Education and Arts
Faculty of Education and Arts
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Open Access Status
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File Access
Controlled