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標題: 以最鄰近相似度為基礎的穩健分群方法
A Nearest Neighbor Similarity based Method for Robust Clustering
作者: 卓俊佑
Cho, Chun-You
關鍵字: cluster analysis;群集分析;nearest neighbor similarities;clustering;最鄰近相似度;分群
出版社: 電機工程學系所
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This research first discusses several problems that often occur in conventional clustering analysis. The capability of solving these problems can be used as the performance index of clustering methods. Then basic theories of several conventional clustering methods are reviewed and the survey of advantages and disadvantages is included. Based on these discussions, we introduce a nearest neighbor similarity-based robust clustering method (NN-SCM) by discovering the fundamental structure of the data set. Finally, several different data sets are used to compare the performances of the proposed approach and the traditional similarity-based clustering method. Simulation results indicate that the proposed approach has better clustering performance with less computation time while avoiding most of the conventional clustering problems.
其他識別: U0005-2808200713134300
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