Understanding what drives the price of a vehicle is critical for both buyers and sellers. In today’s post, we use scraped data from WeBuyCars listings and use a machine learning model to identify the features that most significantly impact vehicle pricing. As an example, we use a decision tree model to assess what features tend to matter most for raising the price of a vehicle beyond R500 000.
As one would expect, the make and model of car are very important, as are things like mileage and the age of the car (‘year’) and indicators of size. Interestingly, mileage is a less important predictor at lower price thresholds. If you would like to see results for other thresholds, feel free to contact us at Codera.
Compiled by Johan Hanekom
And shared by Codera
