Decision Forests for Classification, Regression, Density Estimation, Manifold Learning and Semi-Supervised Learning

This technical report from Microsoft Research is an A-Z tutorial on how decision tree machine learning algorithms work.  It includes in depth explanations of random forests, extra tree classifiers, random ferns and other variations for both classification and regression.

It is in report format and compares decision forests to other types of machine learning algorithms such as SVM.  Some simple toy problems give the basics and some real life applications such as body position recognition and medical image are included.

There is also an accompanying PowerPoint with some nice animations.

http://research.microsoft.com/pubs/155552/decisionForests_MSR_TR_2011_114.pdf is not available