This competition is basically to gauge the understanding of Machine Learning Workflow and Regression technique in specific.
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. Size of training set: 8534 records Size of test set: 2135 records
Features 1 . ID: Contiguous sample number
2 . Airline: The name of the airline
3 . Date_of_Journey: The date of the journey
4 . Source: The source from which the service begins
5 . Destination: The destination where the service ends
6 . Dep_Time: The time when the journey starts from the source.
7 . Arrival_Time: Time of arrival at the destination.
8 . Duration: Total duration of the flight.
9 . Total_Stops: Total stops between the source and destination.
10 . Additional_Info: Additional information about the flight
Target Price: The price of the ticket