Abstract
Cars are being sold more than ever. Developing countries adopt the lease culture instead of buying a new car due to affordability. Therefore, the rise of used cars sales is exponentially increasing. Car sellers sometimes take advantage of this scenario by listing unrealistic prices owing to the demand. Therefore, arises a need for a model that can assign a price for a vehicle by evaluating its features taking the prices of other cars into consideration. In this paper, we use supervised learning method, namely, Random Forest to predict the prices of used cars. The model has been chosen after careful exploratory data analysis to determine the impact of each feature on price. A Random Forest with 500 Decision Trees were created to train the data. From experimental results, the training accuracy was found out to be 95.82%, and the testing accuracy was 83.63%. The model can predict the price of cars accurately by choosing the most correlated features.
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References
Strauss, O.T., Hansen, M.S.: Advanced data science systems and methods useful for auction pricing optimization over network. U.S. Patent Application No. 15/213,941
Zhang, X., Zhang, Z., Qiu, C.: Model of predicting the price range of used car (2017)
Awad, W.A., ELseuofi, S.M.: Machine learning method for spam-email classification (2011)
Srivastava, D.K., Bhambhu, L.: Data classification method using support vector machine (2009)
Pudaruth, S.: Predicting the price of used cars using machine learning techniques. Int. J. Inf. Comput. Technol. 4(7), 753–764 (2014)
Noor, K., Jan, S.: Vehicle price prediction system using machine learning techniques. Int. J. Comput. Appl. 167(9) (2017)
Kuiper, S.: Introduction to multiple regression: how much is your car worth? J. Stat. Educ. 16(3) (2008)
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Pal, N., Arora, P., Kohli, P., Sundararaman, D., Palakurthy, S.S. (2019). How Much Is My Car Worth? A Methodology for Predicting Used Cars’ Prices Using Random Forest. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Advances in Information and Communication Networks. FICC 2018. Advances in Intelligent Systems and Computing, vol 886. Springer, Cham. https://doi.org/10.1007/978-3-030-03402-3_28
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DOI: https://doi.org/10.1007/978-3-030-03402-3_28
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