Abstract
In the paper, we focus on how to get parallel reducts. We present a new method based on matrix of attribute significance, by which we can get parallel reduct as well as dynamic reduct. We prove the validity of our method in theory. The time complex of our method is polynomial. Experiments show that our method has advantages of dynamic reducts. © 2010 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Deng, D., Yan, D., & Wang, J. (2010). Parallel reducts based on attribute significance. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6401 LNAI, pp. 336–343). https://doi.org/10.1007/978-3-642-16248-0_49
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