Feature selection for traditional Malay Musical Instruments sounds classification using rough set

Finding the most relevant features are crucial in data mining task including musical instruments sounds classification problem. Various feature selection techniques have been proposed in this domain focusing on Western musical instruments. However, study on rough set theory for feature selection of...

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Bibliographic Details
Main Authors: Senan, Norhalina, Ibrahim, Rosziati, Mohd Nawi, Nazri, Riyadi Yanto , Iwan Tri, Herawan, Tutut
Format: Article
Published: 2011
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Online Access:http://eprints.uthm.edu.my/2962/
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Summary:Finding the most relevant features are crucial in data mining task including musical instruments sounds classification problem. Various feature selection techniques have been proposed in this domain focusing on Western musical instruments. However, study on rough set theory for feature selection of non-Western musical instruments sounds is insufficient ans still needs further exploration. Thus, in this paper, an alternative feature selection technique using maximum modelling process comprises eight phases: data acquisition, sound editing, data representation, feature extraction, data discretization, data cleansing, feature selection using the proposed technique and finally features evaluation via classifier. The results show that the selected features generated from the proposed technique able to reduce the complexity process and improve the classification performance significantly.