| GENETIC ALGORITHMS AS A STRATEGY FOR FEATURE SELECTION |
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| 引用本文： | R.LEARDI,R.BOGGIA,M.TERRILE. GENETIC ALGORITHMS AS A STRATEGY FOR FEATURE SELECTION[J]. 地理学报(英文版), 1992, 0(5) |
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| 作者姓名： | R.LEARDI R.BOGGIA M.TERRILE |
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| 作者单位： | Istitute di Analisi e Tecnologie Farmaceutiche ed Alimentari Via Brigata Salerno(Ponte) I-16147 Genova Italy，Istitute di Analisi e Tecnologie Farmaceutiche ed Alimentari Via Brigata Salerno(Ponte) I-16147 Genova Italy，Istitute di Analisi e Tecnologie Farmaceutiche ed Alimentari Via Brigata Salerno(Ponte) I-16147 Genova Italy |
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| 摘 要： | Genetic algorithms have been created as an optimization strategy to be used especially when complexresponse surfaces do not allow the use of better-known methods (simplex, experimental designtechniques, etc.). This paper shows that these algorithms, conveniently modified, can also be a valuabletool in solving the feature selection problem. The subsets of variables selected by genetic algorithms aregenerally more efficient than those obtained by classical methods of feature selection, since they canproduce a better result by using a lower number of features.
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GENETIC ALGORITHMS AS A STRATEGY FOR FEATURE SELECTION |
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| R. LEARDI,R. BOGGIA,M. TERRILE,Istitute di Analisi e Tecnologie Farmaceutiche ed Alimentari,Via Brigata Salerno. GENETIC ALGORITHMS AS A STRATEGY FOR FEATURE SELECTION[J]. Journal of Geographical Sciences, 1992, 0(5) |
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| Authors: | R. LEARDI R. BOGGIA M. TERRILE Istitute di Analisi e Tecnologie Farmaceutiche ed Alimentari Via Brigata Salerno |
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| Abstract: | Genetic algorithms have been created as an optimization strategy to be used especially when complex response surfaces do not allow the use of better-known methods (simplex, experimental design techniques, etc.). This paper shows that these algorithms, conveniently modified, can also be a valuable tool in solving the feature selection problem. The subsets of variables selected by genetic algorithms are generally more efficient than those obtained by classical methods of feature selection, since they can produce a better result by using a lower number of features. |
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| Keywords: | Genetic algorithms Feature selection Multivariate analysis Optimization methods |
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