Optimal column subset selection for image classification by genetic algorithms

Pavel Krömer (), Jan Platoš (), Jana Nowaková () and Václav Snášel ()
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Pavel Krömer: VŠB-Technical University of Ostrava
Jan Platoš: VŠB-Technical University of Ostrava
Jana Nowaková: VŠB-Technical University of Ostrava
Václav Snášel: VŠB-Technical University of Ostrava

Annals of Operations Research, 2018, vol. 265, issue 2, No 3, 205-222

Abstract: Abstract Many problems in operations research can be solved by combinatorial optimization. Fixed-length subset selection is a family of combinatorial optimization problems that involve selection of a set of unique objects from a larger superset. Feature selection, p-median problem, and column subset selection problem are three examples of hard problems that involve search for fixed-length subsets. Due to their high complexity, exact algorithms are often infeasible to solve real-world instances of these problems and approximate methods based on various heuristic and metaheuristic (e.g. nature-inspired) approaches are often employed. Selecting column subsets from massive data matrices is an important technique useful for construction of compressed representations and low rank approximations of high-dimensional data. Search for an optimal subset of exactly k columns of a matrix, $$A^{m\times n}$$ A m × n , $$k

Keywords: Column subset selection; Galgorithms; Dimensionality reduction; Feature selection; Classification (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s10479-016-2331-0

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