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- W2077208834 abstract "When compared to standard clustering, fuzzy clustering provides more flexible and powerful data representation. Most fuzzy methods require setting some parameters, as is the case for the Graded Possibilistic c-Means clustering method, which has two parameters in addition to number of centroids. However, for this model selection task there is no well established criterion available. Building on our own previous work on fuzzy clustering similarity indexes, we introduce a technique to evaluate the stability of clusterings by using the fuzzy Jaccard index, and use this procedure to select the most suitable values of parameters. The experiments indicate that the procedure is effective for fuzzy and possibilistic clustering." @default.
- W2077208834 created "2016-06-24" @default.
- W2077208834 creator A5042789365 @default.
- W2077208834 creator A5078310289 @default.
- W2077208834 date "2014-09-01" @default.
- W2077208834 modified "2023-09-24" @default.
- W2077208834 title "Visual stability analysis for model selection in graded possibilistic clustering" @default.
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- W2077208834 doi "https://doi.org/10.1016/j.ins.2014.01.031" @default.
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