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Using Random Forest to Learn Imbalanced Data

Using Random Forest to Learn Imbalanced Data

statistics.berkeley.edu

2.1 Random Forest Random forest (Breiman, 2001) is an ensemble of unpruned classification or regression trees, induced from bootstrap samples of the training data, using random feature selection in the tree induction process. Predic-tion is made by aggregating (majority vote for classification or averaging for regression) the predictions of

  Forest, Random, Random forests, Random forest random forest

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