Periodic Data with Machine Learning (Like Degree Angles -> 179 is 2 different from -179)

Question

I\'m using Python for kernel density estimations and gaussian mixture models to rank likelihood of samples of multidimensional data. Every piece of data is an angle, and I\'m no

Answer 1

An alternative to the methods already posted would be to model the angular variables using the Von Mises distribution.

This distribution appears to be supported by scipy so shouldn't be too difficult to fit into a mixture model.