Supervised Classification and Mathematical Optimization

Emilio Carrizosa, Dolores Romero Morales

Research output: Contribution to journalJournal articleResearchpeer-review


Data mining techniques often ask for the resolution of optimization problems. Supervised classification, and, in particular, support vector machines, can be seen as a paradigmatic instance. In this paper, some links between mathematical optimization methods and supervised classification are emphasized. It is shown that many different areas of mathematical optimization play a central role in off-the-shelf supervised classification methods. Moreover, mathematical optimization turns out to be extremely useful to address important issues in classification, such as identifying relevant variables, improving the interpretability of classifiers or dealing with vagueness/noise in the data.
Original languageEnglish
JournalComputers & Operations Research
Issue number1
Pages (from-to)150–165
Publication statusPublished - 2013
Externally publishedYes

Cite this