Mathematical programming based heuristics for improving LP-generated classifiers for the multiclass supervised classification problem

Mathematical programming based heuristics for improving LP-generated classifiers for the multiclass supervised classification problem

0.00 Avg rating0 Votes
Article ID: iaor20063538
Country: Netherlands
Volume: 168
Issue: 1
Start Page Number: 181
End Page Number: 199
Publication Date: Jan 2006
Journal: European Journal of Operational Research
Authors: ,
Keywords: heuristics, programming: integer
Abstract:

Mathematical programming is used as a nonparametric approach to supervised classification. However, mathematical programming formulations that minimize the number of misclassifications on the design dataset suffer from computational difficulties. We present mathematical programming based heuristics for finding classifiers with a small number of misclassifications on the design dataset with multiple classes. The basic idea is to improve an LP-generated classifier with respect to the number of misclassifications on the design dataset. The heuristics are evaluated computationally on both simulated and real world datasets.

Reviews

Required fields are marked *. Your email address will not be published.