Constrained Classification: The Use of a Priori Information in Cluster Analysis

PSYCHOMETRIKA--VOL. 49, NO. 2, 187--215

29 Pages Posted: 24 May 2016

See all articles by Wayne S. DeSarbo

Wayne S. DeSarbo

Pennsylvania State University

Vijay Mahajan

University of Texas at Austin - Department of Information, Risk and Operations Management

Date Written: June 1984

Abstract

In many classification problems, one often possesses external and/or internal information concerning the objects or units to be analyzed which makes it appropriate to impose constraints on the set of allowable classifications and their characteristics. CONCLUS, or CONstrained CLUStering, is a new methodology devised to perform constrained classification in either an overlapping or nonoverlapping (hierarchical or nonhierarchial) manner. This paper initially reviews the related classification literature. A discussion of the use of constraints in clustering problems is then presented. The CONCLUS model and algorithm are described in detail, as well as their flexibility for use in various applications. Monte Carlo results are presented for two synthetic data sets with appropriate discussion of the resulting implications. An illustration of CONCLUS is presented with respect to a sales territory design problem where the objects classified are various Forbes-500 companies. Finally, the discussion section highlights the main contribution of the paper and offers some areas for future research.

Keywords: Cluster Analysis, Constrained Optimization

Suggested Citation

DeSarbo, Wayne S. and Mahajan, Vijay, Constrained Classification: The Use of a Priori Information in Cluster Analysis (June 1984). PSYCHOMETRIKA--VOL. 49, NO. 2, 187--215, Available at SSRN: https://ssrn.com/abstract=2783440

Wayne S. DeSarbo (Contact Author)

Pennsylvania State University ( email )

University Park
State College, PA 16802
United States

Vijay Mahajan

University of Texas at Austin - Department of Information, Risk and Operations Management ( email )

Red McCombs School of Business
2100 Speedway, #B6600
Austin, TX 78712
United States

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