I’m not surprised by #1 or #8, but I’m pleasantly surprised by the fact that Leo Breimans paper on Random Forest is still so high up there.

The algorithm is great in its simplicity and it’s mind if mind-blowing how a collective of mostly poor predictors can be used to create an ensemble that is generally predictive. It’s also so much less data intensive and energy intensive to train than a deep learning algorithm.