Overview of flight delay prediction

In this chapter, we will implement a logistic regression-based machine learning model to predict flight delays. This model learns from flight data described in the next section, Flight dataset at a glance. 

A real-life situation goes like this—travel company T has a new prediction feature in their booking system that is designed to enhance a customer's travel experience. How so? For example, say traveler X wants to get on Southwest flight SW1 from origin A (St Louis) to destination C (Denver) with a connection at city B (Chicago). If T's flight booking system could predict the odds of X's flight arriving late at Chicago, and furthermore the odds of missing the connecting flight as well, X has information at their disposal that lets him or her decide the next course of action. 

With these opening point made, let's take a look at our flight dataset. 

The flight dataset at a glance

Data analysis in this chapter relies on a flight dataset, a dataset consisting...