This paper, we propose a fuzzy clustering-based on aggregate attribute method for classification tasks, which comprises three phases: (1) Calculate the aggregate attribute values. (2) Apply fuzzy clustering to cluster the aggregate values. (3) Predict the testing data's class. For verifying proposed method, we use two datasets to illustrate our performance, the datasets are: (1) Iris; (2) Wisconsin-breast-cancer dataset. Finally, we compare with other methods; it is shown that our proposed method is better than other methods. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Wang, J. W., & Cheng, C. H. (2006). Fuzzy clustering-based on aggregate attribute method. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4031 LNAI, pp. 478–487). Springer Verlag. https://doi.org/10.1007/11779568_52
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