Abstract
Indiscernibility relation and attribute reduction criteria are the important concepts in rough sets, also are the important base for further researching on attribute reduction. By analyzing the set theory background of indiscernibility and the reduction theory, it can be seen that an information system has the similar characteristics relative to a relation database table and can be analyzed using its data table structure. Combining the structure information of the system with the rough sets reduction theory, a simple reduction analysis can be completed and get useful reduction information. Such as whether a system has redundant attributes or not and how many attributes are need by the system to maintaining its classes, etc. The analysis is realized by a simple algorithm: PARA, the algorithm together with an effective heuristics algorithm can decide an area of the minimum reduct. It greatly reduces the searching area of finding minimum reduct and can play some role in high-dimensionality reduction. A given example shows the algorithm.
The project is supported by Guangdong Natural Science Foundation (China) (No.04009480, No.06301299) and Appropriative Researching Fund for Professors and Doctors, Guangdong Institute of Education ARF(GDEI).
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Xu, N., Zhang, Y., Yu, Y. (2007). A Simple Reduction Analysis and Algorithm Using Rough Sets. In: Kryszkiewicz, M., Peters, J.F., Rybinski, H., Skowron, A. (eds) Rough Sets and Intelligent Systems Paradigms. RSEISP 2007. Lecture Notes in Computer Science(), vol 4585. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73451-2_35
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DOI: https://doi.org/10.1007/978-3-540-73451-2_35
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