Discretization method for equipment quality data

DOI:	10.11809/bqzbgcxb2023.09.018
Keywords:	equipment quality; data discretization; data mining; data preprocessing; association rule
Abstract:	Data mining technology has become an important means of using equipment data resources to obtain knowledge. Data preprocessing is an important part of equipment quality information analysis. In order to solve the problem that data types do not adapt to data mining methods, a discrete method for equipment quality data is proposed. The principle and process of the classical class attribute interdependency maximization algorithm are introduced, the existing problems are analyzed, and the modification method is proposed. Rough set theory and attribute resolution are introduced to limit over discretization, and attribute importance evaluation method is proposed to reduce information loss. The comparative experimental results show that the method proposed in this paper has advantages and can improve the effect of data discretization. Taking a certain type of equipment as an example, the method proposed in this paper is applied to the data preprocessing before association rule mining, and the knowledge related to the rule of quality change in the equipment life cycle is obtained, which verifies the effectiveness of the method.
Issue:	Vol. 44 No. 9 (2023)
Published:	2023-09-28
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