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Відбір змінних в логістичну регресію генетичним алгоритмом
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UDC: 62-50:15
Publication Language: Russian
Stuc. intelekt. 2008; 13(3): 714-719
Abstract: In the paper we discuss effective procedures for а feature selection problem in a binary logistic regression model. A genetic algorithm was used to find best feature combinations, with the special fitness function based on a penalty parameter for including new variables. This parameter depends on ROC-curve index on current epoch. Experiments on Madelon data set and credit scoring classification problem were made.
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