MILP approach to pattern generation in logical analysis of data

Authors:
Hong Seo Ryoo;In-Yong Jang
Affiliations:
Division of Information Management Engineering & Graduate School of Information Management and Security, Korea University, 1, 5-Ka, Anam-Dong, Seongbuk-Ku, Seoul, 136-713, Republic of Korea;Division of Information Management Engineering & Graduate School of Information Management and Security, Korea University, 1, 5-Ka, Anam-Dong, Seongbuk-Ku, Seoul, 136-713, Republic of Korea
Venue:
Discrete Applied Mathematics
Year:
2009

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Abstract

Pattern generation methods for the Logical Analysis of Data (LAD) have been term-enumerative in nature. In this paper, we present a Mixed 0-1 Integer and Linear Programming (MILP) approach that can identify LAD patterns that are optimal with respect to various previously studied and new pattern selection preferences. Via art of formulation, the MILP-based method can generate optimal patterns that also satisfy user-specified requirements on prevalence, homogeneity and complexity. Considering that MILP problems with hundreds of 0-1 variables are easily solved nowadays, the proposed method presents an efficient way of generating useful patterns for LAD. With extensive experiments on benchmark datasets, we demonstrate the utility of the MILP-based pattern generation.