Mathematical Programming for Data Mining: Formulations and Challenges (1998)
| Venue: | INFORMS Journal on Computing |
| Citations: | 40 - 0 self |
BibTeX
@ARTICLE{Bradley98mathematicalprogramming,
author = {P. S. Bradley and Usama M. Fayyad and O. L. Mangasarian},
title = {Mathematical Programming for Data Mining: Formulations and Challenges},
journal = {INFORMS Journal on Computing},
year = {1998},
volume = {11},
pages = {217--238}
}
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Abstract
This paper is intended to serve as an overview of a rapidly emerging research and applications area. In addition to providing a general overview, motivating the importance of data mining problems within the area of knowledge discovery in databases, our aim is to list some of the pressing research challenges, and outline opportunities for contributions by the optimization research communities. Towards these goals, we include formulations of the basic categories of data mining methods as optimization problems. We also provide examples of successful mathematical programming approaches to some data mining problems. keywords: data analysis, data mining, mathematical programming methods, challenges for massive data sets, classification, clustering, prediction, optimization. To appear: INFORMS: Journal of Compting, special issue on Data Mining, A. Basu and B. Golden (guest editors). Also appears as Mathematical Programming Technical Report 98-01, Computer Sciences Department, University of Wi...
