Bagging Matlab. The statistical technique of bagging to reduce the variance of a classification or regression procedureA playlist of these Machine Learning videos is ava. For details about the differences between TreeBagger and bagged ensembles ClassificationBaggedEnsemble and RegressionBaggedEnsemble see Comparison of TreeBagger and Bagged Ensembles.
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The curve starts at approximately 23 which is the fraction of unique observations selected by one bootstrap replica and goes down to 0 at approximately 10 trees. Also TreeBagger selects a random subset of predictors to use at each decision split as in the random. The OOBIndices property of TreeBagger tracks which observations are out of bag for what trees.
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Every tree in the ensemble is grown on an independently drawn bootstrap replica of input data. In general combining multiple classification models increases predictive performance. The bootstrap method for estimating statistical. Yfit is a cell array of character vectors for classification and a numeric array for regression.
