Geodesic
On the Problem Related to Reductive Attributes in the Incomplete Decision Tables
Serdica Journal of Computing, Tome 16 (2022) no. 1, pp. 24-38.

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Attribute reduction is a key problem in the process of data mining and knowledge discovery. Up to now, many attribute reduction algorithms in incomplete decision tables have been proposed. However, the research results related to conditional attributes and reduct of incomplete decision tables are still limited. By relational database approach, this paper investigates some properties of conditional attributes and proposes an algorithm to determine all reductive attributes of consistent incomplete decision tables in polynomial time. The proposed algorithm is an effective tool to eliminate all redundant attributes in data pre-processing in order to improve the efficiency of data mining models.
Keywords: Incomplete Decision System, Attribute Reduction, Reduct, Reductive Attribute 
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Demetrovics, Janos; Giang, Nguyen Long; Thi, Vu Duc; Anh, Pham Viet. On the Problem Related to Reductive Attributes in the Incomplete Decision Tables. Serdica Journal of Computing, Tome 16 (2022) no. 1, pp. 24-38. http://geodesic.mathdoc.fr/item/SJC_2022_16_1_a0/