Artificial Immune Recognition System with Nonlinear Resource Allocation Method and Application to Traditional Malay Music Genre Classification

Authors:
Shahram Golzari;Shyamala Doraisamy;Md Nasir Sulaiman;Nur Izura Udzir;Noris Mohd. Norowi
Affiliations:
Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang, Malaysia 43400 and Electrical and Computer Engineering Department, Hormozgan University, Bandarabbas, Ir ...;Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang, Malaysia 43400;Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang, Malaysia 43400;Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang, Malaysia 43400;Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang, Malaysia 43400
Venue:
ICARIS '08 Proceedings of the 7th international conference on Artificial Immune Systems
Year:
2008

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Abstract

Artificial Immune Recognition System (AIRS) has shown an effective performance on several machine learning problems. In this study, the resource allocation method of AIRS was changed with a nonlinear method. This new algorithm, AIRS with nonlinear resource allocation method, was used as a classifier in Traditional Malay Music (TMM) genre classification. Music genre classification has a great important role in music information retrieval systems nowadays. The proposed system consists of three stages: feature extraction, feature selection and finally using proposed algorithm as a classifier. Based on results of conducted experiments, the obtained classification accuracy of proposed system is 88.6 % using 10 fold cross validation for TMM genre classification. The results also show that AIRS with nonlinear allocation method obtains maximum classification accuracy for TMM genre classification.