Presentation 2005/7/20
A Hybrid Real-Coded Genetic Algorithm with Pruning
Hong ZHANG, Masumi ISHIKAWA,
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Abstract(in English) In this paper, we propose a novel method that introduces pruning into the proposed hybrid real-coded genetic algorithm with local search based on the regularization for acquaring a classification model with good generalization. Consequently, it is able to expect to obtain a classfication model which has higher generalization. To demonstrate effectiveness of the proposed method, we carry out simulation experiments on iris classification problem. Based on the Spearman's rank correlation coefficient between the classification rates of obtained classification models for training data and test data, we investigate the performance of the classification models obtained.
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Keyword(in English) real-coded genetic algorithm / local search / global search / pattern classification / generalization / pruning
Paper # NC2005-32
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Committee NC
Conference Date 2005/7/20(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Hybrid Real-Coded Genetic Algorithm with Pruning
Sub Title (in English)
Keyword(1) real-coded genetic algorithm
Keyword(2) local search
Keyword(3) global search
Keyword(4) pattern classification
Keyword(5) generalization
Keyword(6) pruning
1st Author's Name Hong ZHANG
1st Author's Affiliation Graduate School of Life Science & Systems Engineering Kyushu Institute of Technology()
2nd Author's Name Masumi ISHIKAWA
2nd Author's Affiliation Graduate School of Life Science & Systems Engineering Kyushu Institute of Technology
Date 2005/7/20
Paper # NC2005-32
Volume (vol) vol.105
Number (no) 211
Page pp.pp.-
#Pages 6
Date of Issue