A multiobjective evolutionary setting for feature selection and a commonality-based crossover operator
作者： C. Emmanouilidis , A. Hunter , J. MacIntyre
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摘要: … We argue that this is a generic approach, which can be used … is that there is no reason why the best subset ofp variables, … of non-dominated solutions, without influencing the search. …
lincoln.ac.uk
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sci-hub.se 参考文章(21)
César Guerra-Salcedo, Stephen Chen, Stephen F. Smith, Non-standard crossover for a standard representation--commonality-based feature subset selection genetic and evolutionary computation conference. pp. 129- 134 ,(1999)
J. David Schaffer, Larry J. Eshelman, Preventing Premature Convergence in Genetic Algorithms by Preventing Incest. international conference on genetic algorithms. pp. 115- 122 ,(1991)
Stephen Chen, Stephen F. Smith, Introducing a new advantage of crossover: commonality-based selection genetic and evolutionary computation conference. pp. 122- 128 ,(1999)
Your brains and my beauty: parent matching for constrained optimisation ieee international conference on evolutionary computation. pp. 810- 815 ,(1998) , 10.1109/ICEC.1998.700156
J. Horn, N. Nafpliotis, D.E. Goldberg, A niched Pareto genetic algorithm for multiobjective optimization world congress on computational intelligence. pp. 82- 87 ,(1994) , 10.1109/ICEC.1994.350037
Donald F. Specht, Probabilistic neural networks Neural Networks. ,vol. 3, pp. 109- 118 ,(1990) , 10.1016/0893-6080(90)90049-Q
Alan J. Miller, Subset Selection in Regression ,(2002)
R.Paul Gorman, Terrence J. Sejnowski, Analysis of Hidden Units in a Layered Network Trained to Classify Sonar Targets Neural Networks. ,vol. 1, pp. 75- 89 ,(1988) , 10.1016/0893-6080(88)90023-8
Kenneth N. Berk, Comparing Subset Regression Procedures Technometrics. ,vol. 20, pp. 1- 6 ,(1978) , 10.1080/00401706.1978.10489609
P. Pudil, J. Novovičová, J. Kittler, Floating search methods in feature selection Pattern Recognition Letters. ,vol. 15, pp. 1119- 1125 ,(1994) , 10.1016/0167-8655(94)90127-9