Rough Decision Rules and Its Uncertainty Research in Data Mining
Yongquan Yu
Abstract
Yongquan Yu
Abstract
The evaluation of the uncertainty of rough decision rules in data analyzing needs proper uncertainty measures.Several methods of measuring rough decision rules are discussed and an information entropy-based uncertainty measures are presented based on variable precision rough set theory,which can deal with the two aspects of uncertainty of rules,namely inconsistency and randomness.Also they consider the influence of the noise in the data upon the consistency of the rules and can propose nearly consistent rules.A simple example is used to compareγ0,Hdetand HVPRS,illustrating that HVPRSis better for evaluating rough decision rules.
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The evaluation of the uncertainty of rough decision rules in data analyzing needs proper uncertainty measures.Several methods of measuring rough decision rules are discussed and an information entropy-based uncertainty measures are presented based on variable precision rough set theory,which can deal with the two aspects of uncertainty of rules,namely inconsistency and randomness.Also they consider the influence of the noise in the data upon the consistency of the rules and can propose nearly consistent rules.A simple example is used to compareγ0,Hdetand HVPRS,illustrating that HVPRSis better for evaluating rough decision rules.
Key concepts: Rough set, Computer science, Data mining, Decision rule, Dominance-based rough set approach, Randomness, Consistency (knowledge bases), Entropy (arrow of time)