An application of a GA with Markov network surrogate to feature selection

DOI10.1080/00207721.2012.684449zbMath1305.90092OpenAlexW1992597081WikidataQ62043654 ScholiaQ62043654MaRDI QIDQ5172496

Alexander E. I. Brownlee, John A. W. McCall, Stewart Massie, Stefan Stulajter, Olivier Regnier-Coudert

Publication date: 4 February 2015

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207721.2012.684449

zbMATH Keywords

genetic algorithmssurrogate modelsMarkov networkscase base reasoningfitness approximation

Mathematics Subject Classification ID

Stochastic network models in operations research (90B15) Approximation methods and heuristics in mathematical programming (90C59)

Related Items (3)

Learnheuristics: hybridizing metaheuristics with machine learning for optimization with dynamic inputs ⋮ An efficient optimum Latin hypercube sampling technique based on sequencing optimisation using simulated annealing ⋮ Optimal Kullback–Leibler approximation of Markov chains via nuclear norm regularisation

Uses Software

• UCI-ml

Cites Work

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• Hybrid estimation of distribution algorithm for global optimization
• Gene selection for cancer classification using support vector machines

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