Separation of data via concurrently determined discriminant functions

Hong Seo Ryoo; Kwangsoo Kim

Separation of data via concurrently determined discriminant functions

School of Industrial Management Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper presents a mixed 0-1 integer and linear programming (MILP) model for separation of data via a finite number of nonlinear and nonconvex discriminant functions. The MILP model concurrently optimizes the parameters of the user-provided individual discriminant functions and implements a decision boundary for an optimal separation of data under analysis. The MILP model is extensively tested on six well-studied datasets in data mining research. The comparison of numerical results by the MILP-based classification of data with those produced by the multisurface method and the support vector machine in these experiments and the best from the literature illustrates the efficacy and the usefulness of the new MILP-based classification of data for supervised learning.

Original language	English
Title of host publication	Theory and Applications of Models of Computation - 4th International Conference, TAMC 2007, Proceedings
Pages	533-541
Number of pages	9
Publication status	Published - 2007
Event	4th International Conference on Theory and Applications of Models of Computation, TAMC 2007 - Shanghai, China Duration: 2007 May 22 → 2007 May 25

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4484 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	4th International Conference on Theory and Applications of Models of Computation, TAMC 2007
Country/Territory	China
City	Shanghai
Period	07/5/22 → 07/5/25

Keywords

Data classification
Machine learning
Mixed integer and linear programming

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Cite this

Ryoo, H. S., & Kim, K. (2007). Separation of data via concurrently determined discriminant functions. In Theory and Applications of Models of Computation - 4th International Conference, TAMC 2007, Proceedings (pp. 533-541). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4484 LNCS).

Separation of data via concurrently determined discriminant functions. / Ryoo, Hong Seo; Kim, Kwangsoo.

Theory and Applications of Models of Computation - 4th International Conference, TAMC 2007, Proceedings. 2007. p. 533-541 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4484 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ryoo, HS & Kim, K 2007, Separation of data via concurrently determined discriminant functions. in Theory and Applications of Models of Computation - 4th International Conference, TAMC 2007, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4484 LNCS, pp. 533-541, 4th International Conference on Theory and Applications of Models of Computation, TAMC 2007, Shanghai, China, 07/5/22.

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Separation of data via concurrently determined discriminant functions

Abstract

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Keywords

ASJC Scopus subject areas

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