Abstract
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 theoryfor 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.
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Senan, N., Ibrahim, R., Nawi, N.M., Yanto, I.T.R., Herawan, T. (2010). Soft Set Theory for Feature Selection of Traditional Malay Musical Instrument Sounds. In: Zhu, R., Zhang, Y., Liu, B., Liu, C. (eds) Information Computing and Applications. ICICA 2010. Lecture Notes in Computer Science, vol 6377. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16167-4_33
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DOI: https://doi.org/10.1007/978-3-642-16167-4_33
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