Correlation Research of Association Rules and Application in the Data about Coronary Heart Disease
Zhengkui Lin, Weiguo Yi, Mingyu Lu, Zhi Liu, Hao Xu · 2009
The mining association rule is an important research field in data mining. The mining association rule usually adopts this model: support, confidence, interestingness. But this model can't measure the correlative degree between the antecedent and the consequent of the rule by ration. So we proposed a new mining model of association rules: support, coincidence, interestingness and analyzed the meaning of coincidence by instance. At last, we used this model in the data about coronary heart disease and obtained a lot of meaningful rules.