DRF: A Random Forest for (almost) everything

When Breiman introduced the Random Forest (RF) algorithm in 2001, did he know the tremendous effect it would have? Nowadays RF is a heavily used tool in many parts of data science. It’s easy to see why — RF is easy-to-use and known for its high performance in an extremely wide range of tasks. This alone is impressive, but what makes it even more interesting is that no tuning is generally required to …

data science deep-dives non-parametric probability-distributions random random-forest