Juan Felix Avila Herrera

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Logical Analysis of Data (LAD) is a supervised learning algorithm which integrates principles of combinatorics, optimization and the theory of Boolean functions. Current implementations of LAD use greedy-type heuristics to select patterns to form an LAD model. In this paper we present a new approach based on integer programming and network flows to identify(More)
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(More)
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