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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/37160


    Title: Robust Clustering based on Winner-Population Markov Chain
    Authors: Yang, Fu-wen;Lin, Hwei-jen;Wang, Patrick, S. P.;Wu, Hung-hsuan
    Contributors: 淡江大學資訊工程學系
    Date: 2006-08-20
    Issue Date: 2010-01-11 12:30:56 (UTC+8)
    Abstract: In this paper, we propose an unsupervised genetic clustering algorithm, which produces a new chromosome without any conventional genetic operators, and instead according to the gene reproducing probabilities determined by Markov chain modeling. Selection of cluster centers from the dataset enables construction of a look-up table that saves the distances between all pairs of data points. The experimental results show that the proposed algorithm not only solves the premature problem to provide a more stable clustering performance in terms of number of clusters and clustering results, but also improves the time efficiency
    Relation: Proceedings of the 18th International Conference on Pattern Recognition (ICPR2006), pp.589-592
    DOI: 10.1109/ICPR.2006.1002
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Proceeding

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