In this chapter, we shall use the gradient boosted trees and random forest implementation as pre-made estimators in TensorFlow from the Google TensorFlow team. Let us learn the details of their implementation in the upcoming sections.
Decision tree-based ensembles in TensorFlow
TensorForest Estimator
TensorForest is a highly scalable implementation of random forests built by combining a variety of online HoeffdingTree algorithms with the extremely randomized approach.
Google published the details of the TensorForest implementation in the following paper: TensorForest: Scalable Random Forests on TensorFlow by Thomas Colthurst, D. Sculley, Gibert Hendry, Zack Nado, presented at Machine Learning...