講題: Robust cluster validity indexes

演講者：吳國龍 教授(崑山科技大學資訊管理系)

Abstract : Cluster validity indexes can be used to evaluate the fitness of data partitions produced by a clustering algorithm and are usually independent of clustering algorithms. However, the values of validity indexes may be heavily influenced by noise and outliers. These noise and outliers may not influence the results from clustering algorithms, but they may affect the values of validity indexes. In the literature, there is little discussion about the robustness of cluster validity indexes. In this study, we analyze the robustness of a validity index using the function of M-estimate and then propose several robust-type validity indexes. We discuss the validity measure on a single data point and focus on those validity indexes that can be categorized as the mean type of validity indexes. We then propose median-type validity indexes that are robust to noise and outliers. Comparative examples with numerical and real data sets show that the proposed median-type validity indexes work better than the mean-type validity indexes.

時間：2010年11月26日(星期五) 10：30 ∼ 12：00

地點：推廣大樓3樓9313室

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