Car Price Prediction

Objective:

To predict the price of the cars

Metric Used:

Root Mean Square Log Error(RMSLE)

(Ideally a value closer to 0.0 indicates a better performing model.)

Dataset:

• The training dataset consisted of 19,236 rows and 18 columns. The test dataset consisted of 8,245 rows and 18 columns.
• Exploratory Data Analysis - (Link to view code)

Method:

1. Base-line model: Linear Regression Model (Code)

• RMSLE on cross-validation dataset = 1.62
• RMSLE on test dataset = 1.63

2. Final Model: Random Forest Regressor (Code)

• RMSLE on cross-validation dataset = 1.34
• RMLSE on test dataset = 1.45

NOTE:

This project was as part of the MATHCO.THON hackathon hosted by MachineHack and organised by The Math Company. (View details)