Abstract
Attribute reduction is one of the key problems in the theoretical research of Rough Set, and many algorithms have been proposed and studied about it. These methods may be divided into two strategies (addition strategy and deletion strategy), which are based on adopting different heuristics or fitness functions for attribute selection. In this paper, we propose a new algorithm based on frequency of attribute appearing in the discernibility matrix. It takes the core as foundation, and joins the most high frequency attribute in the discernibility matrix, until the discernibility matrix is empty. In order to find optimum Pawlak reduction of decision table, this paper adds the converse eliminate action until it cannot delete. The time complexity of the algorithm in this paper is O(mn 2 ) ,and the testing indicates that the performance of the method proposed in this paper is faster than that of those algorithms.
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Lihe, G. (2007). A New Algorithm for Attribute Reduction Based on Discernibility Matrix. In: Cao, BY. (eds) Fuzzy Information and Engineering. Advances in Soft Computing, vol 40. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71441-5_42
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DOI: https://doi.org/10.1007/978-3-540-71441-5_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-71440-8
Online ISBN: 978-3-540-71441-5
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