www.gusucode.com > stats 源码程序 matlab案例代码 > stats/TrainABaggedEnsembleOfClassificationTreesExample.m
%% Train Bagged Ensemble of Classification Trees %% % Load the |ionosphere| data set. load ionosphere %% % Train a bagged ensemble of 100 classification trees using all % measurements. rng(1) % For reproducibility Mdl = fitensemble(X,Y,'bag',100,'Tree','Type','classification') %% % |Mdl| is a |ClassificationBaggedEnsemble| model object. %% % |Mdl.Trained| is the property that stores a 100-by-1 cell vector % of the trained classification trees (|CompactClassificationTree| model % objects) that compose the ensemble. %% % Plot a graph of the first trained classification tree. view(Mdl.Trained{1},'Mode','graph') %% % By default, |fitensemble| grows deep decision trees for bagged ensembles. %% % Estimate the in-sample misclassification rate. L = resubLoss(Mdl) %% % |L| is 0, which indicates that |Mdl| is perfect at classifying the % training data.