Analysis of user-weighted pi rough k-means

Conference item

Peters, Georg and Lingras, Pawan. (2014). Analysis of user-weighted pi rough k-means. In D Miao, W Pedrycz and D Slezak (Ed.). Rough Sets and Knowledge Technology. Switzerland: Springer. pp. 547 - 556 https://doi.org/10.1007/978-3-319-11740-9_50
AuthorsPeters, Georg and Lingras, Pawan
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.

KeywordsRough k-Means; User-Defined Weights; Soft Clustering
Year2014
PublisherSpringer
Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-319-11740-9_50
Publisher's version
File Access Level
Controlled
Page range547 - 556
Research GroupSchool of Arts
Place of publicationSwitzerland
EditorsD Miao, W Pedrycz and D Slezak
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