Research on Food Consumer Price Index Based on Association Rules and Clustering
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A variety of data mining methods in their daily lives more and more attention, this article through the association rules and clustering, on China's 31 provinces food consumer price index of residents were analyzed. The association rules mainly discover the correlation between the food consumer price classification index. Clustering is based on the food consumer price index of each region and combines its own information to classify the highest similarity into a group. From the difference analysis of consumer price index, we can explore the influencing factors of different regions, so as to provide ideas for regional policy adjustment and benefit the people.
Food consumer price index, Association rules, Apriori algorithm, Clustering analysis