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We propose a new ensemble algorithm called Convex Hull Ensemble Machine (CHEM). CHEM in Hilbert space is first developed and modified for regression and classification problems. We prove that the ensemble model converges to the optimal model in Hilbert space under regularity conditions. Empirical studies reveal that, for classification problems, CHEM has a prediction accuracy similar to that of boosting,...
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 a.s. to a limit as the number of trees in the forest becomes large. The generalization error of a forest of tree classifiers depends on the strength of the individual...
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