Integer programming formulations of statistical classification problems

Integer programming formulations of statistical classification problems

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Article ID: iaor19972592
Country: United Kingdom
Volume: 24
Issue: 6
Start Page Number: 681
End Page Number: 688
Publication Date: Dec 1996
Journal: OMEGA
Authors:
Keywords: programming: integer
Abstract:

A series of approaches is presented to formulate statistical classification problems using integer programming. The formulations attempt to maximize the number of observations that can be properly classified and utilize single function, multiple function and hierarchical multiple function approaches to the problems. The formulations are tested using standard software on a sample problem and new approaches are compared to those of other authors. As the solution of such problems gives rise to various awkward features in an integer programming framework, it is demonstrated that new approaches to formulation will not be completely successful in avoiding the difficulties of existing methods, but demonstrate certain gains.

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