Problem Statement
Simplified version: "Given a destination and a date range, which is a better airport to fly out from - SFO or OAK?"
We wanted to apply machine learning techniques to build a predictive model which can help flyer decide which airport to choose. Our model was built using data for all US domestic flights from 2001-08. Our models works for all airports, however we were particularly interested in SFO/OAK. There is a popular urban myth to fly from OAK to avoid delays. But we find that myth is not true always.
About the Data
We will be working with airline data for individual years found at http://stat-computing.org/dataexpo/2009/the-data.html.
Techniques
Naive Bayes
Logistic Regression
Python Libraries Pandas, Scikit, Matplotlib, Seaborn