Parallel Reducts and Decision System Decomposition
Dayong Deng, Dianxun Yan, Jiyi Wang, Lin Chen
Abstract
Dayong Deng, Dianxun Yan, Jiyi Wang, Lin Chen
Abstract
In this paper, we continue to investigate the properties of parallel reducts. We reveal the drawbacks in the method of decomposing a decision system into a family of decision sub-tables for dynamic reducts, and present a novel method of decomposing a decision system into a series of decision sub-tables for parallel reducts, which also can be applied to dynamic reducts. We prove in theory that the method is effective. Moreover, the method provides a way of calculating the reducts of an inconsistent decision from a family of consistent decision sub-tables, and vice versa.
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In this paper, we continue to investigate the properties of parallel reducts. We reveal the drawbacks in the method of decomposing a decision system into a family of decision sub-tables for dynamic reducts, and present a novel method of decomposing a decision system into a series of decision sub-tables for parallel reducts, which also can be applied to dynamic reducts. We prove in theory that the method is effective. Moreover, the method provides a way of calculating the reducts of an inconsistent decision from a family of consistent decision sub-tables, and vice versa.
Key concepts: Decision system, Decision table, Computer science, Decomposition, Data mining, Decision rule, Decision support system, Rough set