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2002•Jisuanji gongchengRequires access

RESEARCH OF MINIMUM DECISION ALGORITHM BASED ROUGH SET

Zhu Hong

Open publisher page 1 citations

Abstract

In decision table, each line corresponds its decision rule. However, not all condition attributes are needed in decision, which has a lot to be reduced. After the reduction of decision table, there are still possibilities to reduce more, which does no effect on decision. For doing so, we can obtain the minimum rule unit. So the research is of value. Finally, the paper presents a minimum algorithm, which can obtain the mostly-reduced pre-condition attribute unit of its rule, without core-valued table.

About this research paper

What this paper is about

In decision table, each line corresponds its decision rule. However, not all condition attributes are needed in decision, which has a lot to be reduced. After the reduction of decision table, there are still possibilities to reduce more, which does no effect on decision. For doing so, we can obtain the minimum rule unit. So the research is of value. Finally, the paper presents a minimum algorithm, which can obtain the mostly-reduced pre-condition attribute unit of its rule, without core-valued table.

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Key contribution

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Method / approach

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Available abstract

In decision table, each line corresponds its decision rule. However, not all condition attributes are needed in decision, which has a lot to be reduced. After the reduction of decision table, there are still possibilities to reduce more, which does no effect on decision. For doing so, we can obtain the minimum rule unit. So the research is of value. Finally, the paper presents a minimum algorithm, which can obtain the mostly-reduced pre-condition attribute unit of its rule, without core-valued table.

Key concepts: Decision table, Rough set, Computer science, Table (database), Decision rule, Reduction (mathematics), Dominance-based rough set approach, Algorithm

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