Shahrood University of Technology Journal of AI and Data Mining 2322-5211 9 3 2021 07 01 Investigating Changes in Household Consumable Market Using Data Mining Techniques 341 349 2109 10.22044/jadm.2021.10024.2139 EN A. Hasan-Zadeh Fouman Faculty of Engineering, College of Engineering, University of Tehran, Fouman, Iran. F. Asadi Fouman Faculty of Engineering, College of Engineering, University of Tehran, Fouman, Iran. N. Garbazkar Fouman Faculty of Engineering, College of Engineering, University of Tehran, Fouman, Iran. Journal Article 2020 09 01 For an economic review of food prices in May 2019 to determine the trend of rising or decreasing prices compared to previous periods, we considered the price of food items at that time. The types of items consumed during specific periods in urban areas and the whole country are selected for our statistical analysis. Among the various methods of modelling and statistical prediction, and in a new approach, we modeled the data using data mining techniques consisting of decision tree methods, associative rules, and Bayesian law. Then, prediction, validation, and standardization of the accuracy of the validation are performed on them. Results of data validation in the urban and national area and the results of the standardization of the accuracy of validation in the urban and national area are presented with the desired accuracy. data mining Bayesian Rule decision tree Associative Rule Households’ Consumer Goods https://jad.shahroodut.ac.ir/article_2109_72a2a4abec8bd37df0ba92c94f8b4901.pdf