Uncovering surveillance planes with BuzzFeed
From a list of points along a flight's path, how can you say "this looks like a surveillance plane?" And once you've found them, what do you do with the results?
logistic regression feature engineering publishing ethics classification
Readings and links
In 2016, Buzzfeed News published a piece exploring government surveillance planes, which they found by combining a federal plane database with flight tracking information. One year later they followed this investigation up with another piece that used machine learning to uncover potential surveillance planes that weren't listed in the registry.
In this chapter we will dig deep into the process of feature engineering, the process of creating new ways of describing your data that improve the performance of your machine learning algorithms. We'll also explore the difference between using yes/no predictions as compared to probabilities. Most exciting of all, we'll make maps of flight paths!
Notebooks, Assignments, and Walkthroughs
Flight paths come as a series of individual measurements. How do you combine them together to create a profile of the way an individual plane typically flies?
After all this analysis, it's time for a break! Take the suspicious flight paths and draw them on a map.
After the feature engineering has been completed, use a random forest classifier to detect spy planes.