Evolution of superFeatures through genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@Article{journals/es/DayN11,

• author = "Peter Day and Asoke K. Nandi",
• title = "Evolution of superFeatures through genetic programming",
• journal = "Expert Systems",
• year = "2011",
• volume = "28",
• number = "2",
• pages = "167--184",
• publisher = "Blackwell Publishing Ltd",
• keywords = "genetic algorithms, genetic programming, super features, classification, binary string fitness characterisation, comparative partner selection",
• ISSN = "1468-0394",
• DOI = "doi:10.1111/j.1468-0394.2010.00547.x",
• size = "18 pages",
• abstract = "The success of automatic classification is intricately linked with an effective feature selection. Previous studies on the use of genetic programming (GP) to solve classification problems have highlighted its benefits, principally its inherent feature selection (a process that is often performed independent of a learning method). In this paper, the problem of classification is recast as a feature generation problem, where GP is used to evolve programs that allow non-linear combination of features to create superFeatures, from which classification tasks can be achieved fairly easily. In order to generate superFeatures robustly, the binary string fitness characterisation along with the comparative partner selection strategy is introduced with the aim of promoting optimal convergence. The techniques introduced are applied to two illustrative problems first and then to the real-world problem of audio source classification, with competitive results.",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/journals/es/es28.html#DayN11",

}

Genetic Programming entries for Peter Day Asoke K Nandi

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