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When do Random Forests work?

This work revisits decorrelation and regularization by presenting a systematic analysis of out-of-sample mean-squared error (MSE) for different SNR scenarios and finds that, for both bagging and random forests, bias can be significantly reduced in the presence of correlated covariates.

Christos Revelas, O. Boldea, B. Werker · 2 citations

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