Optimization approaches to Supervised Classification

Pedro Silva

European Journal of Operational Research, 2017, vol. 261, issue 2, 772-788

Abstract: The Supervised Classification problem, one of the oldest and most recurrent problems in applied data analysis, has always been analyzed from many different perspectives. When the emphasis is placed on its overall goal of developing classification rules with minimal classification cost, Supervised Classification can be understood as an optimization problem. On the other hand, when the focus is in modeling the uncertainty involved in the classification of future unknown entities, it can be formulated as a statistical problem. Other perspectives that pay particular attention to pattern recognition and machine learning aspects of Supervised Classification have also a long history that has lead to influential insights and different methodologies.

Keywords: Multivariate statistics; Discriminant analysis; Mathematical programming; Support vector machines (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:261:y:2017:i:2:p:772-788

DOI: 10.1016/j.ejor.2017.02.020

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