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International Journal of Database Theory and Application 2011年第3期4卷 59-76页

作者： Senan, Norhalina Ibrahim, Rosziati Nawi, Nazri Mohd Yanto, Iwan Tri Riyadi Herawan, Tutut Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Parit Raja 86400 Batu Pahat Johor Malaysia Department of Mathematics Universitas Ahmad Dahlan Yogyakarta Indonesia Jalan Prof. Dr. Soepomo Janturan Yogyakarta Indonesia Facultyof Computer System and Software Engineering Universiti Malaysia Pahang Lebuh Raya Tun Razak 26300 Gambang Kuantan Pahang Malaysia

Feature selection has become very vital aspect in musical instruments sounds for handling the problem of 'curse of dimensionality'. Various feature selection techniques have been applied in this domain focusing on Western musical instruments sounds. However, study on feature selection using rough sets of non-Western musical instruments sounds including Malay Traditional musical instruments is inadequate and still needs an intensive research. Thus, in this paper, an alternative feature selection technique using rough set theory based on Maximum Degree of dependency of Attributes (MDA) technique for Traditional Malay musical instruments sounds is proposed. The modeling process comprises eight phases: data acquisition, sound editing, data representation, feature extraction, data discretization, data cleansing, feature selection using proposed technique and feature validation via classification. The results show that the performance of the best 17 selected features is increase up to 99.82% and 98.03% with 1-NN and PART classifiers respectively. © Springer-Verlag (2010).

关键词： Rough set theory

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