Consistency rule mining algorithm based on variable precision dominance relation rough set model#br#

Abstract

Abstract: In order to conduct data mining in dominance-based information system with noise data, the modified knowledge granularity is proposed as the uncertainty measure for the improved rough rule set, and the relative reduction of heuristic information attributes is obtained. Then, the consistency rule set is derived basing on the parameter values provided by variable precision dominance relation rough set, analyzing the influential sensitivity degree of parameter values on rule set. Obviously, the consistency rule set obtained by the algorithm has higher certainty and coverage, the inconsistency caused by data noise is also eliminated, thus ensuring the accuracy and rationality of prediction and classification. Instance analysis proves that this algorithm is an effective method for rule acquisition.

Key words: variable precision dominance rough set, consistency rule set, relative rough rule set, relative reduction, threshold
stationary interval

CLC Number:

TP18

TAO Zhi, HU Liu, WANG Dan. Consistency rule mining algorithm based on variable precision dominance relation rough set model#br#[J]. Journal of Civil Aviation University of China, 2021, 39(1): 59-64.

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