Abstract
In this paper we address the issue of predicting the reselling price of cars based on ads extracted from popular websites for reselling cars. To obtain the most accurate predictions, we have used two machine learning algorithms (multiple linear regression and random forest) to build multiple models to reflect the importance of different combinations of features in the final price of the cars. The predictions are generated based on the models trained on the ads extracted from such sites. The developed system provides the user with an interface that allows navigation through ads to assess the fairness of prices compared to the predicted ones.
References
Baumeister, C., Kilian, L., Lee, T.K.: Inside the crystal ball: new approaches to predicting the gasoline price at the pump. CFS Working Paper No. 500 (2015). doi:10.2139/ssrn.2550731
Dasgupta, A., Sun, Y.V., König, I.R., Bailey-Wilson, J.E., Malley, J.D.: Brief review of regression-based and machine learning methods in genetic epidemiology: the Genetic Analysis Workshop 17 experience. Genet. Epidemiol. 35(S1), S5–S11 (2011)
Aditya, S.T., Aditya, P., Vikesh, K.: Game ON! predicting english premier league match outcomes. Stanford University, Project for course CS229 (2013)
Information Portal of the Directorate for Driving Licenses and Vehicle Registrations. http://www.drpciv.ro/info-portal/displayStatistics.do
Potoski, M.: Predicting gold prices. Stanford University. Project for course CS229 (2013)
Cox, D.R.: The regression analysis of binary sequences. J. R. Stat. Soc. Ser. B 820, 215–242 (1958)
Chen, P.: Predicting Car Prices Part 1: Linear Regression. www.datasciencecentral.com/profiles/blogs/predicting-car-prices-part-1-linear-regression
Pudaruth, S.: Predicting the price of used cars using machine learning techniques. Int. J. Inf. Comput. Technol. 4(7), 753–764 (2014)
Voß, S., Lessmann, S.: Resale price prediction in the used car market. Tristan Symposium VIII (2013)
Tabachnick, B.G., Fidell, L.S.: Using Multivariate Statistics, 6th edn. Pearson Education Limited, Boston (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Caciandone, S., Chiru, CG. (2016). Using Machine Learning to Generate Predictions Based on the Information Extracted from Automobile Ads. In: Dichev, C., Agre, G. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2016. Lecture Notes in Computer Science(), vol 9883. Springer, Cham. https://doi.org/10.1007/978-3-319-44748-3_4
Download citation
DOI: https://doi.org/10.1007/978-3-319-44748-3_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-44747-6
Online ISBN: 978-3-319-44748-3
eBook Packages: Computer ScienceComputer Science (R0)