

George Dahl: Machine Learning for March Madness - danger
http://blog.smellthedata.com/2011/02/thoughts-on-modeling-basketball.html

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danger
This paper (referenced in the post) is also relevant. The application is to
NBA basketball:

"Incorporating Side Information into Probabilistic Matrix Factorization Using
Gaussian Processes." Ryan Prescott Adams, George E. Dahl, and Iain Murray. In
Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence,
2010.

Paper: <http://www.cs.toronto.edu/~gdahl/papers/dpmfNBA.pdf>

Code: <http://www.cs.toronto.edu/~rpa/code/dpmf-nba.tgz>

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tlow
He has some good points. I like the one about correlations between team scores
potentially distorting the strength of offenses and defenses in a naive model.

~~~
rohanseth
+1

