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 performance 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.
Original language | English |
---|---|
Title of host publication | ICDM Workshops 2007 - Proceedings of the 17th IEEE International Conference on Data Mining Workshops |
Pages | 253-258 |
Number of pages | 6 |
DOIs | |
Publication status | Published - 1 Dec 2007 |
Externally published | Yes |
Event | 17th IEEE International Conference on Data Mining Workshops, ICDM Workshops 2007 - Omaha, NE, United States Duration: 28 Oct 2007 → 31 Oct 2007 |
Conference
Conference | 17th IEEE International Conference on Data Mining Workshops, ICDM Workshops 2007 |
---|---|
Country/Territory | United States |
City | Omaha, NE |
Period | 28/10/07 → 31/10/07 |
ASJC Scopus subject areas
- General Engineering