Vehicle Price Prediction System using Machine Learning

Vehicle Price Prediction System using Machine Learning

Shorabh Gautam, Pranshu Kumar, Aniket Jaswal, Harshit Pant, Aditya Narayan Sharma, Monika

Department of Computer Science and Engineering Chandigarh University

Mohali, Punjab, India

Abstract— With the evolution of the world and working methods where people are needed to be present at their working locations at a moment’s notice, a lot of people have now become heavily reliant on personal vehicles to suit their needs. But not everyone can afford to buy a new vehicle for themselves and therefore people are looking forward to buying used cars. But buying a worthy used car for the right price can be quite hectic and difficult. There exist a large number of attributes that must always remain under consideration so that the resulting inductions about the price of a used car are reliable and accurate. Prices depend on attributes such as the vehicle’s model, year of manufacture, distance traveled, number of times the vehicle was serviced, color, interior, number of previous owners, etc. Owing to a large number of factors, Vehicle Price Prediction System becomes need of the hour so that one can effectively determine the true value of a used car. This research paper has developed a well-defined model which makes use of different machine learning algorithms like AdaBoostRegressor, MLP Regressor, Decision Tree Regressor, Random Forest Regressor, ExtraTrees Regressor, etc to make reliable predictions. This research paper has also designed a user interface that inputs data from a user and will go on to display the price of a car as per past values.

Keywords— Vehicle Price prediction, Decision Tree Regressor, Random Forest, AdaBoostRegressor, MLP Regressor