NDLI: MuSeRA: Multiple Selectively Recursive Approach towards imbalanced stream data mining

Content Provider	IEEE Xplore Digital Library
Author	Sheng Chen Haibo He Kang Li Desai, S.
Copyright Year	2010
Description	Author affiliation: Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ 07030 USA (Sheng Chen) \|\| Department of Electrical, Computer, and Biomedical Engineering, University of Rhode Island, Kingston, 02881 USA (Haibo He) \|\| School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast, BT7 1NN, Northern Ireland, UK (Kang Li) \|\| U.S. Army RDECOM-ARDEC, Picatinny Arsenal, New Jersey, 07806, USA (Desai, S.)
Abstract	Learning from data streams has inspired considerable interests in recent years due to its wide applications in the fields such as network intrusion detection, credit fraud identification, spam filtering, and many others. Given the fact that most algorithms developed thus far assume the class distribution of the streaming data is relatively balanced, they will inevitably be confronted with severe performance deterioration when handling the imbalanced data streams. Evolved from our previous work SERA (SElectively Recursive Approach), the MuSeRA algorithm is proposed in this paper to deal with the problem of learning from imbalanced data streams. By maintaining an ensemble consisting of hypotheses built upon the coming training data chunks balanced by selectively accommodating previous minority examples, MuSeRA can efficiently learn the target concept of the imbalanced data streams and thus obtain substantial performance improvement compared to our previous work SERA and the existing stream data mining algorithms. Simulation results validate the effectiveness of the proposed MuSeRA algorithm.
Starting Page	1
Ending Page	8
File Size	1148235
Page Count	8
File Format	PDF
ISBN	9781424469161
ISSN	10987576
e-ISBN	9781424469185
DOI	10.1109/IJCNN.2010.5596538
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-18
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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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