淡江大學機構典藏:Item 987654321/55827
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    题名: Detection of Line-Symmetry Clusters
    作者: Hsieh, Yi-Zeng;Su, Mu-Chun;Chou, Chien-Hsing;Wang, Pa-Chun
    贡献者: 淡江大學電機工程學系
    关键词: Cluster analysis;Clustering algorithm;Symmetry;Distance measure
    日期: 2011-08
    上传时间: 2011-08-28 16:54:39 (UTC+8)
    出版者: Kumamoto: I C I C International
    摘要: Many real-world and man-made objects are symmetry. Therefore, it is reasonable to assume that some kinds of symmetry may exist in data clusters. The most common type of symmetry is line symmetry. In this paper, we propose a line symmetry distance measure. Based on the proposed line symmetry distance, a modified version of the K-means algorithm can be used to partition data into clusters with different geometrical shapes. Several data sets are used to test the performance of the proposed modified version of the K-means algorithm incorporated with the line symmetry distance.
    關聯: International Journal of Innovative Computing, Information and Control 7(8), pp.5027-5043
    显示于类别:[電機工程學系暨研究所] 期刊論文

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