Using Linear Regression For Used Car Price Prediction

Year 2023, , 11 - 16, 31.03.2023

Sumeyra Muti , Kazım Yıldız

https://doi.org/10.22399/ijcesen.1070505

Abstract

Abstract:

Recently, there have been studies on the use of machine learning algorithms for price prediction in many different areas such as stock market, rent a house and used car sales. Studies give information about which algorithm is more successful in price prediction using different machine learning methods. The most commonly used method for price prediction is the linear regression model. In our study, we examined the effectiveness of the linear regression model for used car price prediction. In our study, we applied the linear regression model on a data set that includes the features and price information of vehicles in Turkey for the year 2020. As a result, when we selected 1/3 of the data set as the test data, we observed that the R2 score for the prediction success of our model was 73%. More successful results can be obtained with different data sets or a more detailed data preprocessing.

Keywords

Machine Learning, Car Price Prediction, Linear Regression

References

• [1] I. E. Naqa and M. J. Murphy, "What Is Machine Learning?" Machine Learning in Radiation Oncology, Springer, Cham, pp 3-11, 2015, DOI 10.1007/978-3-319-18305-3_1.
• [2] N. S. Özen, S. Saraç and M. Koyuncu, "COVID-19 Vakalarının Makine Öğrenmesi Algoritmaları ile Tahmini: Amerika Birleşik Devletleri Örneği" European Journal of Science and Technology (EJOSAT), no. 22, pp. 134-139, 2021, DOI: 10.31590/ejosat.855113.
• [3] F. F. Haque, A. Abdelgawad, V. P. Yanambaka and K. Yelamarthi, "Crop Yield Analysis Using Machine Learning Algorithms" 2020 IEEE 6th World Forum on Internet of Things (WF-IoT), 2020, pp. 1-2, DOI: 10.1109/WF-IoT48130.2020.9221459.
• [4] I. Hapsari, I. Surjandari and K. , "Visiting Time Prediction Using Machine Learning Regression Algorithm" 2018 6th International Conference on Information and Communication Technology (ICoICT), pp. 495-500, 2018, DOI: 10.1109/ICoICT.2018.8528810.
• [5] N. Nafi’iyah and K. F. Mauladi, "Linear Regression Analysis and SVR in Predicting Motor Vehicle Theft" 2021 International Seminar on Application for Technology of Information and Communication (iSemantic), pp. 54-58, 2021, DOI: 10.1109/ISEMANTIC52711.2021.9573225.
• [6] Ms Kavita and P. Mathur, "Crop Yield Estimation in India Using Machine Learning" 2020 5th International Conference on Computing Communication and Automation (ICCCA), pp. 220-224, 2020, DOI: 10.1109/ICCCA49541.2020.9250915.
• [7] J. K. Bae and B. Park, "Using machine learning algorithms for housing price prediction: The case of Fairfax County, Virginia housing data", Expert systems with applications, vol. 42, no. 6, pp. 2928-2934, 2015, DOI: 10.1016/j.eswa.2014.11.040.
• [8] A. Varma, A. Sarma, S. Doshi and R. Nair, "House Price Prediction Using Machine Learning and Neural Networks" 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT), pp. 1936-1939, 2018, DOI: 10.1109/ICICCT.2018.8473231.
• [9] I. Imran, U. Zaman, M. Waqar, A. Zaman "Using Machine Learning Algorithms for Housing Price Prediction: The Case of Islamabad Housing Data" Soft Computing and Machine Intelligence, vol. 1, no. 1, pp. 11-23, 2021.
• [10] B. Jia, "Computer mathematical statistics applied in the housing price investigation through machine learning and linear regression model" 2021 International Conference on Data Science and Computer Application (ICDSCA), pp. 769-772, 2021, DOI: 10.1109/ICDSCA53499.2021.9650136.
• [11] C. K.-S. Leung, R. K. MacKinnon and Y. Wang, "A machine learning approach for stock price prediction" IDEAS '14: Proceedings of the 18th International Database Engineering & Applications Symposium, pp. 274-277, 2014, DOI:10.1145/2628194.2628211.
• [12] Z. D. Akşehir and E. Kılıç, "Makine Öğrenmesi Teknikleri ile Banka Hisse Senetlerinin Fiyat Tahmini" Türkiye Bilişim Vakfı Bilgisayar Bilimleri ve Mühendisliği Dergisi, vol. 12, no. 2, pp. 30, 2019.
• [13] M. Nikou, G. Mansourfar, and J. Bagherzadeh “Stock price prediction using DEEP learning algorithm and its comparison with machine learning algorithms” Intelligent Systems in Accounting, Finance and Management, vol. 26, no. 4, pp. 164-174, 2019, DOI: 10.1002/isaf.1459.
• [14] W. Lu, W. Ge, R. Li and L. Yang, "A Comparative Study on the Individual Stock Price Prediction with the Application of Neural Network Models" 2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI), pp. 235-238, 2021, DOI: 10.1109/ICCEAI52939.2021.00046, DOI: 10.1109/ICCEAI52939.2021.00046.
• [15] B. Panwar and P. J. Gaurav Dhuriya, "Stock Market Prediction Using Linear Regression and SVM" 2021 International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE), pp. 629-631, 2021, DOI: 10.1109/ICACITE51222.2021.9404733.
• [16] V. Siddhi, S. Valecha and M. Shreya, "Bitcoin price prediction using machine learning" 2018 20th International Conference on Advanced Communication Technology (ICACT), pp. 144-147, 2018, DOI: 10.23919/ICACT.2018.8323676.
• [17] P. R. Kalehbasti, L. Nikolenko and H. Rezaei, "Airbnb Price Prediction Using Machine Learning and Sentiment Analysis" International Cross-Domain Conference for Machine Learning and Knowledge Extraction, pp. 173-184, 2021, DOI: 10.1007/978-3-030-84060-0_11.
• [18] E. Gegic, B. Isakovic, D. Keco, Z. Masetic and J. Kevric, "Car Price Prediction using Machine Learning Techniques" TEM Journal, vol. 8, no. 1, pp 113, 2019, DOI: 10.18421/TEM81-16.
• [19] S. Selvaratnam, B. Yogarajah, T. Jeyamugan and N. Ratnarajah, "Feature selection in automobile price prediction: An integrated approach" 2021 International Research Conference on Smart Computing and Systems Engineering (SCSE), vol. 4, pp. 106-112, 2021, DOI: 10.1109/SCSE53661.2021.9568288.
• [20] E. NAMLI, E. GÜL and R. ÜNLÜ, "FİYAT TAHMİNLEMESİNDE MAKİNE ÖĞRENMESİ TEKNİKLERİ VE DOĞRUSAL REGRESYON" Konya Mühendislik Bilimleri Dergisi, vol. 7, pp. 806-821, 2019, DOI: 10.36306/konjes.654952. [21] Ö. ÇELİK and U. Ö. OSMANOĞLU, "Prediction of The Prices of Second-Hand Cars" European Journal of Science and Technology (EJOSAT), no. 16, pp. 77-83, 2019, DOI: 10.31590/ejosat.542884.
• [22] KAGGLE (10.10.2021), https://www.kaggle.com/alpertemel/turkey-car-market-2020.
• [23] G. V. Rossum, Python Development Team “Python Tutorial Release 3.8.1” The Python Software Foundation, 2020.
• [24] L. Moreira, C. Dantas, L. Oliveira, J. Soares and E. Ogasawara, "On Evaluating Data Preprocessing Methods for Machine Learning Models for Flight Delays" 2018 International Joint Conference on Neural Networks (IJCNN), pp. 1-8, 2018, DOI: 10.1109/IJCNN.2018.8489294.
• [25] D. Chicco, M. J. Warrens and G. Jurman, "The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation" PeerJ Computer Science, vol. 7, 2021, DOI: 10.7717/peerj-cs.623.