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- W71651665 abstract "When compared to crisp clustering, fuzzy clustering provides more flexible and powerful data representation. However, most fuzzy methods require setting some parameters, as is the case for our 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." @default.
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- W71651665 date "2011-01-01" @default.
- W71651665 modified "2023-09-23" @default.
- W71651665 title "Tuning Graded Possibilistic Clustering by Visual Stability Analysis" @default.
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- W71651665 doi "https://doi.org/10.1007/978-3-642-23713-3_21" @default.
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