A Rough Set-Based Hierarchical Clustering Algorithm for Categorical Data
作者： Zhu-Rong Wang , Duo Chen , Du-Wu Cui , Chao-Xue Wang
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摘要: In this paper, rough set theory is applied to the clustering analysis. The decision table formed through introduction of attribute into data table, thereby further defining membership matrix. consistent degree and aggregate are present, their functions in process deeply analyzed. level calculation formula designed, which two factors such as taken comprehensive account. Also, paper gives categorical similarity measure based on Euclidean distance so better solve problem difficult measurement because non-numerical nature. On basis above work, a
参考文章(13)
Zdzisław Pawlak, Rough Sets: Theoretical Aspects of Reasoning about Data ,(1991)
Usama M. Fayyad, Paul S. Bradley, Refining Initial Points for K-Means Clustering international conference on machine learning. pp. 91- 99 ,(1998)
Wen-Xiu Zhang, Ju-Sheng Mi, Wei-Zhi Wu, Approaches to knowledge reductions in inconsistent systems International Journal of Intelligent Systems. ,vol. 18, pp. 989- 1000 ,(2003) , 10.1002/INT.10128
Ryszard S. Michalski, Robert E. Stepp, Automated Construction of Classifications: Conceptual Clustering Versus Numerical Taxonomy IEEE Transactions on Pattern Analysis and Machine Intelligence. ,vol. PAMI-5, pp. 396- 410 ,(1983) , 10.1109/TPAMI.1983.4767409
Ying Sun, Qiuming Zhu, Zhengxin Chen, An iterative initial-points refinement algorithm for categorical data clustering Pattern Recognition Letters. ,vol. 23, pp. 875- 884 ,(2002) , 10.1016/S0167-8655(01)00163-5
Dae-Won Kim, Kwang H Lee, Doheon Lee, Fuzzy clustering of categorical data using fuzzy centroids Pattern Recognition Letters. ,vol. 25, pp. 1263- 1271 ,(2004) , 10.1016/J.PATREC.2004.04.004
Sudipto Guha, Rajeev Rastogi, Kyuseok Shim, Rock: A robust clustering algorithm for categorical attributes Information Systems. ,vol. 25, pp. 345- 366 ,(2000) , 10.1016/S0306-4379(00)00022-3
Douglas H. Fisher, Knowledge acquisition via incremental conceptual clustering Machine Learning. ,vol. 2, pp. 139- 172 ,(1987) , 10.1023/A:1022852608280
L. Talavera, J. Bejar, Generality-based conceptual clustering with probabilistic concepts IEEE Transactions on Pattern Analysis and Machine Intelligence. ,vol. 23, pp. 196- 206 ,(2001) , 10.1109/34.908969
Zhexue Huang, Michael K Ng, A fuzzy k-modes algorithm for clustering categorical data IEEE Transactions on Fuzzy Systems. ,vol. 7, pp. 446- 452 ,(1999) , 10.1109/91.784206