www.gusucode.com > stats 源码程序 matlab案例代码 > stats/ReduceSizeOfBagOfTreesExample.m
%% Reduce Size of Bag of Trees % Create a compact bag of trees for efficiently making % predictions on new data. %% % Load the |ionosphere| data set. load ionosphere %% % Train a bag of 100 classification trees using all measurements and the % |AdaBoostM1| method. Mdl = TreeBagger(100,X,Y,'Method','classification') %% % |Mdl| is a |TreeBagger| model object that contains the % training data, among other things. %% % Create a compact version of |Mdl|. CMdl = compact(Mdl) %% % |CMdl| is a |CompactTreeBagger| model object. |CMdl| % is almost the same as |Mdl|. One exception is that it does not store the % training data. %% % Compare the amounts of space consumed by |Mdl| and |CMdl|. mdlInfo = whos('Mdl'); cMdlInfo = whos('CMdl'); [mdlInfo.bytes cMdlInfo.bytes] %% % |Mdl| consumes more space than |CMdl|. %% % |CMdl.Trees| stores the trained classification trees % (|CompactClassificationTree| model objects) that compose |Mdl|. %% % Display a graph of the first tree in the compact model. view(CMdl.Trees{1},'Mode','graph'); %% % By default, |TreeBagger| grows deep trees. %% % Predict the label of the mean of |X| using the compact ensemble. predMeanX = predict(CMdl,mean(X))