Classification as Regression: `fitcensemble` Split Criter

Classification problem parsed as regression problem when Split Criterion is supplied to fitcensemble

char-aditya asked: 2022-05-10 AI, Data Science, and Statistics , Statistics and Machine Learning Toolbox

Facing a classification problem in MATLAB? Learn how supplying a split criterion to fitcensemble can cause it to be parsed as a regression problem. Get the solu

Expert Answer

John Williams answered . 2025-07-14 13:49:56

This is a bug in the search space for hyperparameter optimization in fitcensemble, which will cause it to evaluate some unnecessary points. During the optimization, whenever 'Method' is LogitBoost or GentleBoost, 'SplitCriterion' is always internally set to 'mse'. But the search space is defined in a way that doesn't acknowledge that, so it unnecessarily passes SplitCrierion values of 'gdi' and 'deviance' during the optimization.

So all points that you see with LogitBoost/gdi and LogitBoost/deviance are really just LogitBoost/mse.

Oddly, you are not allowed to explicitly specify 'SplitCriterion','mse' with fitcensemble. Instead, when LogitBoost or GentleBoost are used, you need to omit the SplitCriterion argument entirely.

The optimization results are still valid. You just need to adjust what arguments you pass to fitcensemble at the end. The simple fix in your case is to delete line 8 of your original code sample, which specifies the SplitCriterion. Here's the result:

load carsmall
X = table(Acceleration,Cylinders,Displacement,Horsepower,Mfg,Model_Year,Weight,MPG);

X.Cylinders(X.Cylinders < 8) = 0;  % Create two classes in the Cylinders variable

t = templateTree(  'MaxNumSplits', 30,...
                    'MinLeafSize', 10);

classificationEnsemble = fitcensemble(X,'Cylinders',...
    'Method', 'LogitBoost', ...
    'NumLearningCycles',12,...
    'Learners',t,...
    'KFold',7,...
    'LearnRate',0.1);

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