Flight Ticket Price Prediction

• Flight ticket prices can be something hard to guess, today we might see a price, check out the price of the same flight tomorrow, it will be a different story. We might have often heard travellers saying that flight ticket prices are so unpredictable.
• Here you will be provided with prices of flight tickets for various airlines between the months of March and June of 2019 and between various cities.

Data Overview

Here each data point corresponds to trip of flight from one city to another.

• Airline: The name of the airline.

• Date_of_Journey: The date of the journey

• Source: The source from which the service begins.

• Destination: The destination where the service ends.

• Route: The route taken by the flight to reach the destination.

• Dep_Time: The time when the journey starts from the source.

• Arrival_Time: Time of arrival at the destination.

• Duration: Total duration of the flight.

• Total_Stops: Total stops between the source and destination.

• Additional_Info: Additional information about the flight

• Price(target): The price of the ticket

Type of Machine Learning task :

It is an regression problem where given a set of features we need to predict the price of ticket from one city to another.

Performace Metric

Since it is an regression problem we will use Root Mean Squared error (RMSE) and R-squared as regression metric.