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1 - Oregon State University

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Tree-Based MethodsAdvantages Flexible Model ComplexityControlled by depth of tree Can handle discrete,ordered, and continuousvariablesNo normalization or rescalingneeded Can handle missing valuesProportional distributionSurrogate splits Best “off the shelf” method(Breiman)Disadvantages Poor probability estimates Does not supporthypothesis testing Cannot handle latentvariables High variance, which canbe addressed by Boosting Bagging Randomization10TAAI 201111/11/2011

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