NDLI: Classification by Rough Set Reducts, AdaBoost and SVM

Content Provider	IEEE Xplore Digital Library
Author	Ishii, N. Morioka, Y. Suyama, S. Yongguang Bao
Copyright Year	2010
Abstract	Most classification studies are done by using all the objects data. It is expected to classify objects by using some subsets data in the total data. A rough set based reduct is a minimal subset of features, which has almost the same discernible power as the entire conditional features. Here, we propose a greedy algorithm to compute a set of rough set reducts which is followed by the k-nearest neighbor to classify documents. To improve the classification performance, reducts-kNN with confidence was developed. These proposed rough set reduct based methods are compared with the classification by AdaBoost and SVM(Support Vector Machine) methods. Experiments have been conducted on some benchmark datasets from the Reuters 21578 data set.
Starting Page	63
Ending Page	68
File Size	275082
Page Count	6
File Format	PDF
ISBN	9781424474226
e-ISBN	9781424474219
DOI	10.1109/SNPD.2010.19
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-06-09
Publisher Place	United Kingdom
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Greedy algorithms Data analysis SVM classification Distributed computing Information systems Support vector machines AdaBoost rough set reducts Support vector machine classification Rough sets Machine learning Artificial intelligence Software engineering
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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