Comparative analysis of clustering algorithms
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Abstract
The mathematical formulation of the problem of goods’ categorization is represented, the following stages of its decision are pointed out: indexing, classification and evaluation. Experimental study of classifiers (naive Bayes classifier, SVM method and decision tree) has shown that SVM method is the most effective to solve the problem of categorization.
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References
F. Sebastiani, “A tutorial on automated text categorisation”, in Proceedings of the 1st ArgentinianSymposium on Artificial Intelligence (ASAI’99), 1999, pp. 7–34.
Y. Kalnybolotsky and M. Didkovskaya, “Creative component in the solutionintellectual tasks (structuringproblems)”, Electronics and communication, no. 6, pp. 63–71, Jan. 2008.
D. D. Lewis, “Naive (Bayes) at forty: The independence assumption in information retrieval”, in Machine Learning: ECML-98, Berlin, Heidelberg: Springer Berlin Heidelberg, 1998, pp. 4–15. DOI:10.1007/BFb0026666
C. Apté, F. Damerau, and S. M. Weiss, “Automated learning of decision rules for text categorization”, ACM Transactions on Information Systems, vol. 12, no. 3, pp. 233–251, Jul. 1994. DOI:10.1145/183422.183423
G. Salton, A. Wong, and C. S. Yang, “A vector space model for automatic indexing”, Communications of the ACM, vol. 18, no. 11, pp. 613–620, Nov. 1975. DOI:10.1145/361219.361220
