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Bias Reduction in Split Variable Selection in C4.5
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 Title & Authors
Bias Reduction in Split Variable Selection in C4.5
Shin, Sung-Chul; Jeong, Yeon-Joo; Song, Moon Sup;
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 Abstract
In this short communication we discuss the bias problem of C4.5 in split variable selection and suggest a method to reduce the variable selection bias among categorical predictor variables. A penalty proportional to the number of categories is applied to the splitting criterion gain of C4.5. The results of empirical comparisons show that the proposed modification of C4.5 reduces the size of classification trees.
 Keywords
classification tree;entropy;gain;gain ratio;
 Language
Korean
 Cited by
1.
데이터마이닝 알고리즘을 이용한 제품수명주기 예측 : 의류산업 적용사례,이슬기;강지훈;이한규;주태우;오시연;박성욱;김성범;

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