This paper critically analyzes reduct construction methods at two levels. At a high level, one can abstract commonalities from the existing algorithms, and classify them into three basic groups based on the underlying control structures. At a low level, by adopting different heuristics or fitness functions for attribute selection, one is able to derive most of the existing algorithms. The analysis brings new insights into the problem of reduct construction, and provides guidelines for the design of new algorithms. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Yao, Y., Zhao, Y., & Wang, J. (2006). On reduct construction algorithms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4062 LNAI, pp. 297–304). Springer Verlag. https://doi.org/10.1007/11795131_43
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