[www.researchgate.net/publication/230766603_How_Many_Trees_in_a_Random_Forest](https://www.researchgate.net/publication/230766603_How_Many_Trees_in_a_Random_Forest)

Oshiro, Perez, Baranauskas

University of Michigan - Ann Arbor

A study on different data sizes and different forest sizes (# of attributes) found that at a certian point, increasing the forest size becomes much more computationally expensive without any significant performance gain. 

The study found using between 64 and 128 attributes was an optimal number, with fewer being less accurate, and more slower with similar accuracy. 

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