Random Forests Model
(Redirected from random forest)
Jump to navigation
Jump to search
A Random Forests Model is an ensemble decision tree model (composed of decisions tree models) produced by a random forest training system.
- Context:
- It can range from being a Random Forests Classification Model to being a Random Forests Ranking Model to being a Random Forests Regression Model.
- See: Gradient Boosted Tree Model.
References
2001
- (Breiman, 2001) ⇒ Leo Breiman. (2001). “Random Forests.” In: Machine Learning, 45(1). doi:10.1023/A:1010933404324
- QUOTE: Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. The generalization error for forests converges as to a limit as the number of trees in the forest becomes large.