PREDICTION OF SELLING PRICE OF VARIOUS CARS
Mr.Harshal Kishor Chawhan
Department of Master of Computer Application,
G H Raisoni University , Amravati, India
Received on: 11 May ,2024 Revised on: 18 June ,2024 Published on: 29 June ,2024
Abstract – Predicting the selling price of cars is a complex problem that involves analyzing various factors, including the car’s make, model, year, mileage, condition, and other relevant attributes. This study aims to develop a predictive model that accurately estimates the selling prices of cars using machine learning techniques. By leveraging a dataset containing historical data on car sales, we employ multiple regression analysis and other advanced algorithms to identify patterns and key determinants that influence car prices. The proposed model is validated using a separate test dataset to ensure its accuracy and reliability. The results demonstrate that our model can effectively predict car prices, providing valuable insights for buyers, sellers, and automotive industry stakeholders. This predictive tool can assist in making informed decisions, enhancing market efficiency, and ultimately contributing to a more transparent automotive market.
IndexTerms – Car price prediction, Machine learning, Regression analysis, Automobile market, Predictive modeling, Vehicle valuation, Data analysis, Price determinants, Automotive industry, Market efficiency
Doi Link – https://doi.org/10.69758/GIMRJ2406I8V12P099
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