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- W2162571198 abstract "In this paper a fuzzy point symmetry based genetic clustering technique (fuzzy-VGAPS) is proposed which can determine the number of clusters present in a data set as well as a good fuzzy partitioning of the data. A new fuzzy cluster validity index, FSym-index, which is based on the newly developed point symmetry based distance is also proposed here. FSym-index provides a measure of goodness of clustering on different fuzzy partitions of a data set. Maximum value of FSym-index corresponds to the proper clustering present in a data set. The flexibility of fuzzy-VGAPS is utilized in conjunction with the fuzzy FSym-index to determine the number of clusters present in a data set as well as a good fuzzy partition of the data. The results of the fuzzy VGAPS are compared with those obtained by fuzzy version of variable string length genetic clustering technique (fuzzy-VGA) optimizing XB-index. The effectiveness of the fuzzy-VGAPS is demonstrated on four artificial data sets and two real-life data sets" @default.
- W2162571198 created "2016-06-24" @default.
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- W2162571198 date "2007-03-01" @default.
- W2162571198 modified "2023-10-13" @default.
- W2162571198 title "A Fuzzy Genetic Clustering Technique Using a New Symmetry Based Distance for Automatic Evolution of Clusters" @default.
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- W2162571198 doi "https://doi.org/10.1109/iccta.2007.5" @default.
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