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Fuzzy Clustering-Based on Aggregate Attribute Method

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Advances in Applied Artificial Intelligence (IEA/AIE 2006)

Abstract

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.

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© 2006 Springer-Verlag Berlin Heidelberg

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Wang, JW., Cheng, CH. (2006). Fuzzy Clustering-Based on Aggregate Attribute Method. In: Ali, M., Dapoigny, R. (eds) Advances in Applied Artificial Intelligence. IEA/AIE 2006. Lecture Notes in Computer Science(), vol 4031. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11779568_52

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  • DOI: https://doi.org/10.1007/11779568_52

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-35453-6

  • Online ISBN: 978-3-540-35454-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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