Complex analysis of united states flight data using a data mining approach
Baluch Megan, Bergstra Tristan, Mohamad El-Hajj · 2017
On an average day in the United States, thousands of commercial flights make their way through more than 5,000,000 square miles of U.S airspace. People rely on these flights for business and pleasure needs. Flying can be a very frustrating experience. Data mining past flight data can help consumers make informed decisions about many aspects of flying such as when the best days to fly are and out of which airports? We also wish to find how time is made up for in the air during late flights and how airport size relates to efficiency? Using data mining techniques such as classification, clustering and decision tree algorithms, we hope to be able to predict when you are most likely to encounter delays and increase the knowledge for consumers advising them on the best and most efficient ways to travel.