Abstract
Dynamic reducts with large stability coefficients are good candidates for decision rules generation but it is time consuming to generate them. This paper presents an algorithm dReducts using a cascading hash function to generate (F, ε)-dynamic reducts. With the cascading hash function, an F-dynamic reduct can be generated in O(m 2 n) time with O(mn) space where m and n are total number of attributes and total number of instances of the table. Empirical results of generating (F, ε)-dynamic reducts using five of ten most popular UCI datasets are presented and they are compared to the Rough Set Exploration System (RSES).
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Wang, PC. (2010). Generate (F, ε)-Dynamic Reduct Using Cascading Hashes. In: Yu, J., Greco, S., Lingras, P., Wang, G., Skowron, A. (eds) Rough Set and Knowledge Technology. RSKT 2010. Lecture Notes in Computer Science(), vol 6401. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16248-0_14
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DOI: https://doi.org/10.1007/978-3-642-16248-0_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16247-3
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