Consistency of Online Random Forests

Denil, Misha, Matheson, David, de Freitas, Nando

arXiv.org Machine Learning 

As a testament to their success, the theory of random forests has long been outpaced by their application in practice. In this paper, we take a step towards narrowing this gap by providing a consistency result for online random forests.

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