Novel Method of Knowledge Database Data Mining by Association Rules Extraction Technology in Decision Tree

Abstract

The extraction method of association rules is to find frequent itemset pattern knowledge from a given dataset. In the decision tree method, the example set is regarded as a discrete information system, and its information is represented by information entropy. In this paper, the theory and algorithm of association rules in data mining technology and decision tree are systematically studied, the theoretical model is established, the corresponding association rules mining algorithms are designed, and the simulation experiments of these algorithms are carried out. The paper presents novel method of knowledge database data mining by association rules extraction technology in decision Tree.