International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 48 - Issue 22 |
Published: June 2012 |
Authors: Devashree Rai, Kesari Verma, A. S. Thoke |
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Devashree Rai, Kesari Verma, A. S. Thoke . Classification Algorithm based on MS Apriori for Rare Classes. International Journal of Computer Applications. 48, 22 (June 2012), 52-56. DOI=10.5120/7516-0599
@article{ 10.5120/7516-0599, author = { Devashree Rai,Kesari Verma,A. S. Thoke }, title = { Classification Algorithm based on MS Apriori for Rare Classes }, journal = { International Journal of Computer Applications }, year = { 2012 }, volume = { 48 }, number = { 22 }, pages = { 52-56 }, doi = { 10.5120/7516-0599 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2012 %A Devashree Rai %A Kesari Verma %A A. S. Thoke %T Classification Algorithm based on MS Apriori for Rare Classes%T %J International Journal of Computer Applications %V 48 %N 22 %P 52-56 %R 10.5120/7516-0599 %I Foundation of Computer Science (FCS), NY, USA
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.