MILP approach to pattern generation in logical analysis of data
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Publication:1028471
DOI10.1016/j.dam.2008.07.005zbMath1172.90010OpenAlexW2001731263MaRDI QIDQ1028471
Publication date: 30 June 2009
Published in: Discrete Applied Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.dam.2008.07.005
Applications of mathematical programming (90C90) Mixed integer programming (90C11) Combinatorial optimization (90C27)
Related Items (16)
Graph, clique and facet of Boolean logical polytope ⋮ Data separation via a finite number of discriminant functions: a global optimization approach ⋮ Integrated optimization model and algorithm for pattern generation and selection in logical analysis of data ⋮ Strong valid inequalities for Boolean logical pattern generation ⋮ Logical analysis of multiclass data with relaxed patterns ⋮ Recent advances in the theory and practice of logical analysis of data ⋮ A new column generation algorithm for logical analysis of data ⋮ Simple Pattern Minimality Problems: Integer Linear Programming Formulations and Covering-Based Heuristic Solving Approaches ⋮ On Pareto-optimal Boolean logical patterns for numerical data ⋮ Multi-pattern generation framework for logical analysis of data ⋮ A LAD-based method for selecting short oligo probes for genotyping applications ⋮ Compact MILP models for optimal and Pareto-optimal LAD patterns ⋮ A multi-term, polyhedral relaxation of a 0-1 multilinear function for Boolean logical pattern generation ⋮ \(0\text{-}1\) multilinear programming as a unifying theory for LAD pattern generation ⋮ Spherical classification of data, a new rule-based learning method ⋮ Efficient feature selection for logical analysis of large-scale multi-class datasets
Uses Software
Cites Work
- Logical analysis of data -- an overview: from combinatorial optimization to medical applications
- Occam's razor
- Logical analysis of numerical data
- Global optimization of multiplicative programs
- Pareto-optimal patterns in logical analysis of data
- Support-vector networks
- Very simple classification rules perform well on most commonly used datasets
- Comprehensive vs. comprehensible classifiers in logical analysis of data
- A LAD-based method for selecting short oligo probes for genotyping applications
- Spanned patterns for the logical analysis of data
- State-of-the-Art Survey—Constrained Nonlinear 0–1 Programming
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