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    %% Optimize Regression Ensemble
% This example shows how to optimize hyperparameters automatically using
% |fitrensemble|. The example uses the |carsmall| data.
%%
% Load the data.
load carsmall
%%
% Find hyperparameters that minimize five-fold cross-validation loss by
% using automatic hyperparameter optimization.
%
% For reproducibility, set the random seed and use the
% |'expected-improvement-plus'| acquisition function.
rng(1)
Mdl = fitrensemble([Horsepower,Weight],MPG,'OptimizeHyperparameters','auto',...
    'HyperparameterOptimizationOptions',struct('AcquisitionFunctionName',...
    'expected-improvement-plus'))
%%
% The optimization searched over the methods for regression (|Bag| and
% |LSBoost|), over |NumLearningCycles|, over the |LearnRate| for |LSBoost|,
% and over the tree learner |MinLeafSize|. The output is the ensemble
% regression with the minimum estimated cross-validation loss.