Fuzzy-rough data mining

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Abstract

It is estimated that every 20 months or so the amount of information in the world doubles. In the same way, tools that mine knowledge from data must develop to combat this growth. Fuzzy-rough set theory provides a framework for developing such applications in a way that combines the best properties of fuzzy sets and rough sets, in order to handle uncertainty. In this tutorial we will cover the mathematical groundwork required for an understanding of the data mining methods, before looking at some of the key developments in the area, including feature selection and classifier learning. © 2011 Springer-Verlag.

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Jensen, R. (2011). Fuzzy-rough data mining. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6743 LNAI, pp. 31–35). https://doi.org/10.1007/978-3-642-21881-1_7

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