www.gusucode.com > stats 源码程序 matlab案例代码 > stats/TrainBoostedRegressionEnsembleExample.m
%% Train Boosted Regression Ensemble %% % Load the |ionosphere| data set. load ionosphere %% % Load the |carsmall| data set. Consider a model that explains a car's % fuel economy (|MPG|) using its weight (|Weight|) and number of cylinders % (|Cylinders|). load carsmall X = [Weight Cylinders]; Y = MPG; %% % Train a boosted ensemble of 100 regression trees using the |LSBoost|. % Specify that |Cylinders| is a categorical variable. Mdl = fitensemble(X,Y,'LSBoost',100,'Tree','PredictorNames',{'W','C'},... 'CategoricalPredictors',2) %% % |Mdl| is a |RegressionEnsemble| model object that contains the % training data, among other things. %% % |Mdl.Trained| is the property that stores a 100-by-1 cell vector % of the trained regression trees (|CompactRegressionTree| model % objects) that compose the ensemble. %% % Plot a graph of the first trained regression tree. view(Mdl.Trained{1},'Mode','graph') %% % By default, |fitensemble| grows stumps for boosted ensembles of trees. %% % Predict the fuel economy of 4,000 pound cars with 4, 6, and 8 cylinders. XNew = [4000*ones(3,1) [4; 6; 8]]; mpgNew = predict(Mdl,XNew)