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- W2156890305 abstract "Most of the data mining algorithm focuses on frequent patterns, few algorithm emphases on rare items, but rare items [1] also have importance, for example, network intrusion detection, where among various normal connections we need to detect the rare malicious connections. Classification of such a non-uniform data set is a challenging issue. Most classifiers perform poorly in such a data set. Realizing the importance of rare class classification, in this paper we propose a classification algorithm (CBMR Algorithm) that is based on association rules mined by MSApriori approach [2] and is capable of classifying rare classes. The performance evaluation of the proposed algorithm has been done for different data sets [3] and in comparison with existing technique like [4], it is found that algorithm has efficient and superior performance for classifying rare cases." @default.
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- W2156890305 date "2012-07-03" @default.
- W2156890305 modified "2023-09-30" @default.
- W2156890305 title "Classification Algorithm based on MS Apriori for Rare Classes" @default.
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- W2156890305 doi "https://doi.org/10.5120/7516-0599" @default.
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