Random Forests Authors: Leo Breiman, Adele Cutler
The home site for Random Forest classification algorithm, with resources from its inventors, including the following philosophical note:
RF is an example of a tool that is useful in doing analyses of scientific data.
But the cleverest algorithms are no substitute for human intelligence and knowledge of the data in the problem.
Take the output of random forests not as absolute truth, but as smart computer generated guesses that may be helpful in leading to a deeper understanding of the problem.
I rather like that.
It is applicable to all the inferencing, machine learning, classification, and other tools you will see mentioned in this blog.