Abstract
So far in previous chapters, we have discussed details of various feature selection algorithms, both rough set based and non-rough set based, for supervised learning and unsupervised learning. In this chapter we will provide analysis of different RST-based feature selection algorithms. With explicit discussion on their results, different experiments were performed to compare the performance of algorithms. We will focus on RST-based feature selection algorithms.
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Raza, M.S., Qamar, U. (2017). Critical Analysis of Feature Selection Algorithms. In: Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications. Springer, Singapore. https://doi.org/10.1007/978-981-10-4965-1_7
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DOI: https://doi.org/10.1007/978-981-10-4965-1_7
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