Jui-Hsiang Yang

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A new approach of learning classifiers using genetic programming has been developed recently. Most of the previous researches generate classification rules to classify data. However, the generation of rules is time consuming and the recognition accuracy is limited. In this paper, an approach of learning classification functions by genetic programming is(More)
This paper discusses the feature selection problem upon supervised learning. A learning method based on rough sets and genetic programming is proposed to select significant features and classify numerical data. The proposed method uses rough membership to transform nominal data into numerical values, then selects important features and learns classification(More)
Department of Computer Science and Information Engineering National University of Tainan, Tainan, Taiwan 700, R.O.C. E-mail: bcchien@mail.nutn.edu.tw Department of Information Engineering, I-Shou University Kaohsiung County, Taiwan 840, R.O.C. E-mail: m9003012@isu.edu.tw Department of Computer Science and Information Engineering National University of(More)
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