Transcription of Random Forests - Springer
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Random Forests - Springer
Machine Learning, 45, 5 32, 2001c 2001 Kluwer Academic Publishers. Manufactured in The ForestsLEO BREIMANS tatistics Department, University of California, Berkeley, CA 94720 Editor:Robert E. Forests are a combination of tree predictors such that each tree depends on the values of arandom vector sampled independently and with the same distribution for all trees in the forest. The generalizationerror for Forests converges to a limit as the number of trees in the forest becomes large. The generalizationerror of a forest of tree classifiers depends on the strength of the individual trees in the forest and the corre-lation between them.
2. Characterizing the accuracy of random forests 2.1. Random forests converge Given an ensemble of classifiers h 1(x),h 2(x),...,h K (x), and with the training set drawn at random from the distribution of the random vector Y, X,define the margin function as mg(X,Y) = av k I(h k(X) = Y)−max j=Y av k I(h k(X) = j). where I(·) is the ...
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