Peters, G. & Lingras, P. (2014). Analysis of user-weighted pi rough k-means. D Miao, W Pedrycz, D Slezak. 547-556. Switzerland: Springer. Retrieved from https://doi.org/10.1007/978-3-319-11740-9_50
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.
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