Random Forests provide deeper classification and better predictions Instead of creating a single decision tree, the Random Forest algorithm can create many individual trees from randomly selected ...

Based on this research, Wei Ran Lab has conducted big data analysis, trained millions of samples, and selected the Random Forest algorithm to identify threats in encrypted communication traffic.

The Annals of Statistics, Vol. 43, No. 4 (August 2015), pp. 1716-1741 (26 pages) Random forests are a learning algorithm proposed by Breiman [Mach. Learn. 45 (2001) 5-32] that combines several ...

(ii) automatic sample selection using Machine Learning (Random Forest) techniques for algorithm training using plant height as a discriminating variable; (iii) automatic classification and generation ...

Random Forests can be applied to machine learning — for example, with autonomous cars, what decision process should the algorithm apply if it is about to crash in order to minimise damage, or risk of ...

Cédric Beaulac, Jeffrey S. Rosenthal, Predicting University Students' Academic Success and Major Using Random Forests, Research in Higher Education, Vol. 60, No. 7 (NOVEMBER 2019), pp. 1048-1064 ...