Coverage of all of the methods that we discussed in the lecture and more:
Hastie, T., Tibshirani, R. & Friedman, J. (2009). The Elements of
Statistical Learning: Data Mining, Inference, and Prediction
(Second Edition), NY: Springer.
We didn't discuss theory, but if you're interested in the theory of
(binary) classification, here's a pointer to get you started:
Bartlett, P., Jordan, M. I., & McAuliffe, J. D. (2006).
Convexity, classification and risk bounds. Journal of the
American Statistical Association, 101, 138-156.