A linear programming approach to discriminant analysis with a reserved-judgment region

A linear programming approach to discriminant analysis with a reserved-judgment region

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Article ID: iaor2004437
Country: United States
Volume: 15
Issue: 1
Start Page Number: 23
End Page Number: 41
Publication Date: Jan 2003
Journal: INFORMS Journal On Computing
Authors: , ,
Keywords: programming: network, artificial intelligence
Abstract:

A linear-programming model is proposed for deriving discriminant rules that allow allocation of entitites to a reserved-judgment region. The size of the reserved-judgment region, which can be controlled by varying parameters within the model, dictates the level of aggressiveness (cautiousness) of allocating (misallocating) entities to groups. Results of simulation experiments for various configurations of normal and contaminated normal three-group populations are reported for a variety of parameter selections. Results of cross-validation experiments using real data sets are also reported. Both the simulation and cross-validation experiments include comparison with other discriminant analysis techniques. The results demonstrate that the proposed model is useful for deriving discriminant rules that reduce the chances of misclassification, while maintaining a reasonable level of correct classification.

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