Logical analysis of multi-class data

Logical Analysis of Data (LAD) is a two-class learning algorithm which integrates principles of combinatorics, optimization, and the theory of Boolean functions. This paper proposes an algorithm based on mixed integer linear programming to extend the LAD methodology to solve multi-class classificati...

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Bibliographic Details
Published in2015 Latin American Computing Conference (CLEI) pp. 1 - 10
Main Authors Avila-Herrera, Juan Felix, Mine Subasi, Munevver
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2015
Subjects
Algorithm design and analysis
Benchmark testing
Boolean functions
Data mining
Logical Analysis of Data
Mixed integer linear programming
Multi-class Classification
Optimization
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DOI10.1109/CLEI.2015.7360007

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Summary:Logical Analysis of Data (LAD) is a two-class learning algorithm which integrates principles of combinatorics, optimization, and the theory of Boolean functions. This paper proposes an algorithm based on mixed integer linear programming to extend the LAD methodology to solve multi-class classification problems, where One-vs-All (OvA) learning models are efficiently constructed to classify observations in predefined classes. The utility of the proposed approach is demonstrated through experiments on multi-class benchmark datasets.
DOI:10.1109/CLEI.2015.7360007