Abstract
To reduce the time complexity of attribute reduction algorithm based on discernibility matrix, a simplified decision table is first introduced, and an algorithm with time complexity (| O C||U|) is designed for calculating the simplified decision table. And then, a new measure of the significance of an attribute is defined for reducing the search space of simplified decision table. A recursive algorithm is proposed for computing the attribute significance that its time complexity is of O(|U/C|). Finally, an efficient attribute reduction algorithm is developed based on the attribute significance. This algorithm is equal to existing algorithms in performance and its time complexity is O(|C||U|) +O(|C|2|U/C|)
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Xu, Z., Zhang, C., Zhang, S., Song, W., Yang, B. (2007). Efficient Attribute Reduction Based on Discernibility Matrix. In: Yao, J., Lingras, P., Wu, WZ., Szczuka, M., Cercone, N.J., Ślȩzak, D. (eds) Rough Sets and Knowledge Technology. RSKT 2007. Lecture Notes in Computer Science(), vol 4481. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72458-2_2
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DOI: https://doi.org/10.1007/978-3-540-72458-2_2
Publisher Name: Springer, Berlin, Heidelberg
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