Title of article :
Investigating Changes in Household Consumable Market Using Data Mining Techniques
Author/Authors :
Hasan-Zadeh, Atefeh Fouman Faculty of Engineering - College of Engineering - University of Tehran - Fouman, Iran , Asadi, Faezeh Fouman Faculty of Engineering - College of Engineering - University of Tehran - Fouman, Iran , Garbazkar, Najmeh Fouman Faculty of Engineering - College of Engineering - University of Tehran - Fouman, Iran
Abstract :
For an economic review of the food prices in May 2019 in order to determine the trend of rising or decreasing prices compared to the previous periods, we consider the price of food items at that time. The types of items consumed during specific periods in the 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 model the data using the data mining techniques consisting of the decision tree methods, associative rules, and Bayesian law. Then the prediction, validation, and standardization of the accuracy of the validation are performed on them. The results of data validation in the urban and national area and the results of standardization of the accuracy of validation in the urban and national areas are presented with the desired accuracy.
Keywords :
Data Mining , Bayesian Rule , Decision Tree , Associative Rule , Households’ Consumer Goods
Journal title :
Journal of Artificial Intelligence and Data Mining