NDLI: A Regularized Multiple Criteria Linear Program for Classification

Content Provider	IEEE Xplore Digital Library
Author	Shi, Yong Tian, Yingjie Chen, Xiaojun Zhang, Peng
Copyright Year	2007
Abstract	Although multiple criteria mathematical programs (MCMP), as alternative methods of classification, have been used in various real-life data mining problems, its mathematical structure of solvability are still challenge- able. This paper proposes a regularized multiple criteria linear program (RMCLP) for classification. It first adds some regularization terms in the objective function of the known multiple criteria linear program (MCLP) model for possible existence of solution. Then the paper describes the mathematical framework of the solvability. Finally, a series of experimental tests are conducted to illustrate the perfor- mance of the proposed RMCLP with the existing methods: MCLP, multiple criteria quadratic program (MCQP), and support vector machine (SVM). The results of four publicly available datasets and a real-life credit dataset all show that RMCLP is a competitive method in classification.
Starting Page	253
Ending Page	258
File Size	144884
Page Count	6
File Format	PDF
ISBN	9780769530192
DOI	10.1109/ICDMW.2007.46
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-10-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Information science Content addressable storage Data analysis Conferences Support vector machine classification Linear programming Educational institutions Data mining Testing
Content Type	Text
Resource Type	Article

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