www.gusucode.com > stats 源码程序 matlab案例代码 > stats/PredictorImportanceAndSurrogateSplitsEnsExample.m
%% Predictor Importance and Surrogate Splits % Estimate the predictor importance for all variables in the data and where % the regression tree ensemble contains surrogate splits. %% % Load the |carsmall| data set. load carsmall %% % Grow an ensemble of 100 regression trees for |MPG| using |Acceleration|, |Cylinders|, % |Displacement|, |Horsepower|, |Model_Year|, and |Weight| as predictors. % Specify to identify surrogate splits. X = [Acceleration Cylinders Displacement Horsepower Model_Year Weight]; t = templateTree('Surrogate','on'); ens = fitensemble(X,MPG,'LSBoost',100,t); %% % Estimate the predictor importance and predictive measures of importance % for all predictor variables. [imp,ma] = predictorImportance(ens) %% % Comparing |imp| to the results in <docid:stats_ug.bu4moyj>, |Horsepower| % has the greatest impact on mileage, with |Weight| having the second greatest % impact.