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%% Reduce Memory Consumption of Regression Tree Model % Compare the size of a full regression tree model to the compacted model. %% % Load the |carsmall| data set. Consider |Acceleration|, |Displacement|, % |Horsepower|, and |Weight| as predictor variables. load carsmall X = [Acceleration Cylinders Displacement Horsepower Weight]; %% % Grow a regression tree using the entire data set. Mdl = fitrtree(X,MPG) %% % |Mdl| is a |RegressionTree| model. It is a full model, that is, it % stores information such as the predictor and response data |fitrtree| % used in training. For a properties list of full regression tree models, % see <docid:stats_ug.bstsjqq-1>. %% % Create a compact version of the full regression tree. That is, one that % contains enough information to make predictions only. CMdl = compact(Mdl) %% % |CMdl| is a |CompactRegressionTree| model. For a properties list of % compact regression tree models, see <docid:stats_ug.bst07u_-1>. %% % Inspect the amounts of memory that the full and compact regression trees % consume. mdlInfo = whos('Mdl'); cMdlInfo = whos('CMdl'); [mdlInfo.bytes cMdlInfo.bytes] cMdlInfo.bytes/mdlInfo.bytes %% % In this case, the compact regression tree model consumes about 25% less % memory than the full model consumes.