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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.