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Understanding and Using Rough Set Based Feature Selection: Concepts, Techniques and Applications pp 53–79Cite as

Rough Set Theory

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Abstract

This chapter discusses the basic preliminaries of rough set theory (RST). Since its inception, RST has been a prominent tool for data analysis due to its analysis friendly nature. RST provides a range of data structures, e.g. information systems, decision systems and approximations, to represent the real-world data. Furthermore, it provides various methods to help analyse this data. This chapter discusses the basic concepts of RST with example to set a strong foundation of RST to be used as feature selection.

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  1. Department of Computer Engineering, College of Electrical & Mechanical Engineering, National University of Sciences and Technology (NUST), Rawalpindi, Pakistan

    Muhammad Summair Raza & Usman Qamar

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  1. Muhammad Summair Raza
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  2. Usman Qamar
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Raza, M.S., Qamar, U. (2017). Rough Set Theory. 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_3

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  • DOI: https://doi.org/10.1007/978-981-10-4965-1_3

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