NDLI: Evaluating boosting algorithms to classify rare classes: comparison and improvements

Content Provider	IEEE Xplore Digital Library
Author	Joshi, M.V. Kumar, V. Agarwal, R.C.
Copyright Year	2001
Description	Author affiliation: IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA (Joshi, M.V.)
Abstract	Classification of rare events has many important data mining applications. Boosting is a promising meta-technique that improves the classification performance of any weak classifier. So far, no systematic study has been conducted to evaluate how boosting performs for the task of mining rare classes. The authors evaluate three existing categories of boosting algorithms from the single viewpoint of how they update the example weights in each iteration, and discuss their possible effect on recall and precision of the rare class. We propose enhanced algorithms in two of the categories, and justify their choice of weight updating parameters theoretically. Using some specially designed synthetic datasets, we compare the capability of all the algorithms from the rare class perspective. The results support our qualitative analysis, and also indicate that our enhancements bring an extra capability for achieving better balance between recall and precision in mining rare classes.
Sponsorship	IEEE Comput. Soc. Tech. Committe on Pattern Anal. & Machine Intelligence (TCPAMI)
Starting Page	257
Ending Page	264
File Size	675010
Page Count	8
File Format	PDF
ISBN	0769511198
DOI	10.1109/ICDM.2001.989527
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-11-29
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Boosting Voting Computer science Data mining Performance evaluation Algorithm design and analysis Surges Classification algorithms Costs Error analysis
Content Type	Text
Resource Type	Article

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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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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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