Abstract
Fixed-length subset problems occur where a solution to a problem is described by an unordered subset of a particular cardinality. Some fixed-length subset problems are known as “deceptive” problems. In a deceptive problem certain possible solutions tend to lead the search algorithm towards a locally optimal solution. In this research, deceptive problems are treated as feature selection problems, the goal is to find the right combination of features that solves the problem. We explore a family of genetic search methods known as messy genetic algorithms on artificially generated deceptive problems and real-world instance-based classification problems.
Part of this work was done while the author was visiting researcher at Colorado State University
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© 2001 Springer-Verlag Wien
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Guerra-Salcedo, C.M. (2001). Feature Subset Selection Problems: A Variable-Length Chromosome Perspective. In: Kůrková, V., Neruda, R., Kárný, M., Steele, N.C. (eds) Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6230-9_64
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DOI: https://doi.org/10.1007/978-3-7091-6230-9_64
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-83651-4
Online ISBN: 978-3-7091-6230-9
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