Authorship Patterns via Machine Learning

Although this about music, I like it as an example of pattern recognition, and useful as an exampled.  I note that the link is to the Financial Times, which has a strict pay-wall.   But the example stands as a useful example of this technology use.  Looking up the tech paper, will post here:

Abstract and technical but useful paper here:  https://hdsr.mitpress.mit.edu/pub/xcq8a1v1 

Lennon or McCartney? Machine Learning Tries to Crack Disputed Beatles Authorship 
Financial Times By Martin Coulter

Researchers at Harvard University and Canada's Dalhousie University used machine learning to ascertain the authorship of disputed Beatles songs. Over a three-year period, the team created an algorithm and applied it to an array of musical motifs taken from 70 songs co-authored by Paul McCartney and John Lennon. The algorithm was able to distinguish tracks known to be written by one of the two musicians with 76% accuracy. When applied to eight disputed songs or song segments, the algorithm found a number of the songs yielded a more than 90% match against Lennon's other works; one song was an 81% match for Lennon, with its bridge returning a 57% match for McCartney. Harvard's Mark Glickman hopes the algorithm's statistical model finds use as "a blueprint for those wanting to follow changes in music over time."  .... '