Further reading

Perhaps the most wide-ranging and informative tour of Ensembles and ensemble types is provided by the Kaggle competitor, Triskelion, at http://mlwave.com/kaggle-ensembling-guide/.

For discussion of the Netflix Prize-winning model, Pragmatic Chaos, refer to http://www.stat.osu.edu/~dmsl/GrandPrize2009_BPC_BellKor.pdf. For an explanation by Netflix on how changing business contexts rendered that $1M-model redundant, refer to the Netflix Tech blog at http://techblog.netflix.com/2012/04/netflix-recommendations-beyond-5-stars.html.

For a walkthrough on applying random forest ensembles to commercial contexts, with plenty of space given to all-important diagnostic charts and reasoning, consider Arshavir Blackwell's blog at https://citizennet.com/blog/2012/11/10/random-forests-ensembles-and-performance-metrics/.

For further information on random forests specifically, I find the scikit-learn documentation helpful: http://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier...