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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/98263

    Title: A New Measure of Cluster Validity Using Line Symmetry
    Authors: Chou, Chien-Hsing;Hsieh, Yi-Zeng;Su, Mu-Chun
    Contributors: 淡江大學電機工程學系
    Keywords: cluster validity;clustering algorithm;line symmetry;cluster analysis;similarity measure;unsupervised learning
    Date: 2014-02
    Issue Date: 2014-06-27 23:49:50 (UTC+8)
    Publisher: Taipei: Institute of Information Science
    Abstract: Many real-world and man-made objects are symmetry, therefore, it is reasonable to assume that some kind of symmetry may exist in data clusters. In this paper a new cluster validity measure which adopts a non-metric distance measure based on the idea of "line symmetry" is presented. The proposed validity measure can be applied in finding the number of clusters of different geometrical structures. Several data sets are used to illustrate the performance of the proposed measure.
    Relation: Journal of Information Science and Engineering 30(2), pp.443-461
    Appears in Collections:[電機工程學系暨研究所] 期刊論文

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