Norhalina Senan, Rosziati Ibrahim, Dr. Nazri Mohd Nawi, Iwan Tri Riyadi Yanto, Tutut Herawan. Soft Set Theory for Feature Selection of Traditional Malay Musical Instrument Sounds. In Rongbo Zhu, Yanchun Zhang, Baoxiang Liu, Chunfeng Liu, editors, Information Computing and Applications - First International Conference, ICICA 2010, Tangshan, China, October 15-18, 2010. Proceedings. Volume 6377 of Lecture Notes in Computer Science, pages 253-260, Springer, 2010. [doi]
Computational models of the artificial intelligence such as soft set theory have several applications. Soft data reduction can be considered as a machine learning technique for features selection. In this paper, we present the applicability of soft set theory for feature selection of Traditional Malay musical instrument sounds. The modeling processes consist of three stages: feature extraction, data discretization and finally using the multi-soft sets approach for feature selection through dimensionality reduction in multi-valued domain. The result shows that the obtained features of proposed model are 35 out of 37 attributes.