usedCarPrices

Objective : Predicting used car prices in India.

Notebook

• View / Download the notebook here.
• Run the Notebook on Kaggle here.

Models used

• Linear Regression
• Random Forest Regression
• XGBoost Regression
• Ridge Regression
• Lasso Regression

Dataset Features

• 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.

File Description

• Data_Train.csv : Used for training
• Data_Test.csv : Used for making final predictions
• predictions.csv : Contains the predictions made by XGBoost Regressorr which had the best R2 score.