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used car price prediction using random forest algorithm

  • Unique Paper ID: 162426
  • Volume: 10
  • Issue: 10
  • PageNo: 85-89
  • Abstract:
  • The price of a new car in the industry is fixed by the manufacturer with some additional costs incurred by the Government in the form of taxes. So, customers buying a new car can be assured that money they invest to be worthy. But, due to the increased prices of new cars and the financial incapability of the customers to buy them, used car sales are on a global increase. Therefore, there is an urgent need for a used car price prediction system which effectively determines the worthiness of the car based on multiple aspects, including vehicle mileage, year of manufacturing, fuel consumption, transmission, road tax, fuel type, and engine size. We have developed a model which will be highly effective. This model can benefit sellers, buyers, and car manufacturers in the used cars market. Upon completion, it can output a relatively accurate price prediction based on the information that users input. Random forest algorithms were applied in the research to achieve the highest accuracy. Because of this, it will be possible to predict the actual price of a car rather than the price range of a car. To evaluate the performance of each regression, the R-square was calculated
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 10
  • Issue: 10
  • PageNo: 85-89

used car price prediction using random forest algorithm

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