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Classification Algorithm based on MS Apriori for Rare Classes

by Devashree Rai, Kesari Verma, A. S. Thoke
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 48 - Number 22
Year of Publication: 2012
Authors: Devashree Rai, Kesari Verma, A. S. Thoke
10.5120/7516-0599

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 },
issue_date = { June 2012 },
volume = { 48 },
number = { 22 },
month = { June },
year = { 2012 },
issn = { 0975-8887 },
pages = { 52-56 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume48/number22/7516-0599/ },
doi = { 10.5120/7516-0599 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:44:48.523182+05:30
%A Devashree Rai
%A Kesari Verma
%A A. S. Thoke
%T Classification Algorithm based on MS Apriori for Rare Classes
%J International Journal of Computer Applications
%@ 0975-8887
%V 48
%N 22
%P 52-56
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
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.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Rare Classes Msapriori Algorithm Classification Data Mining

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