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The Data Mining Model that Predicts the Customer Decision-Making in Buying a Car

Journal: International Journal of Computer Science and Mobile Computing - IJCSMC (Vol.8, No. 4)

Publication Date:

Authors : ; ;

Page : 177-181

Keywords : Customer behavior; Market Analysis; Decision Making; Linear Regression; Association rules; Random Forest Classification; Comparison;

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For the last few of decades, India has become one of the largest country in the world in the adaptation and establishment of the automobile industry which growing steadily each year. That is why the decision-making and behavior of a customer become a point of interest. The decision of buying a car constitutes a unique type of buying behavior. This is something different in comparison to the buying or shopping of the essential needs of the life. The main objective to this prediction is to advance the knowledge of what are the factors that influences the customer's choices of the car stores. More specifically, the main focus has been on how different situations (e.g. type of buying) influence the choice of the car stores. The frequent item sets are mined and associated from the market basket database using the efficient algorithm and hence the association rules are generated. The decision tree can be constructed using Linear Regression algorithm and Random Forest Classification algorithm. Then at last the prediction made by the both linear regression algorithm and random forest classification algorithm is compared for the best results.

Last modified: 2019-05-01 23:01:13