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2 claims from 1 paper

1. Mathematics › Statistical Methods and Inference

   Random Forests

   Breiman · Machine Learning · 2001

   Unchecked2 claims
   Show 2 claims

   1. UncheckedAs more trees are added to a random forest, its generalization error settles towards a fixed limit, with probability one.“The generalization error for forests converges a.s. to a limit as the number of trees in the forest becomes large.”
   2. UncheckedA forest of tree classifiers makes more or fewer errors on new data depending on how strong each tree is and how correlated the trees are.“The generalization error of a forest of tree classifiers depends on the strength of the individual trees in the forest and the correlation between them.”