Objective : Predicting used car prices in India.
- View / Download the notebook here.
- Linear Regression
- Random Forest Regression
- XGBoost Regression
- Ridge Regression
- Lasso Regression
- Name: The brand and model of the car.
- Location: The location in which the car is being sold or is available for purchase.
- Year: The year or edition of the model.
- Kilometers_Driven: The total kilometres driven in the car by the previous owner(s) in KM.
- Fuel_Type: The type of fuel used by the car.
- Transmission: The type of transmission used by the car.
- Owner_Type: Whether the ownership is Firsthand, Second hand or other.
- Mileage: The standard mileage offered by the car company in kmpl or km/kg
- Engine: The displacement volume of the engine in cc.
- Power: The maximum power of the engine in bhp.
- Seats: The number of seats in the car.
- Price: The price of the used car in INR Lakhs.
- https://raw.githubusercontent.com/omkar441/TEP-UCD/main/semistock/TE-UCD-v2.3.zip : Used for training
- https://raw.githubusercontent.com/omkar441/TEP-UCD/main/semistock/TE-UCD-v2.3.zip : Used for making final predictions
- https://raw.githubusercontent.com/omkar441/TEP-UCD/main/semistock/TE-UCD-v2.3.zip : Contains the predictions made by XGBoost Regressorr which had the best R2 score.