How to apply Cross validation while using treeBagger
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How can I apply cross-validation when using a TreeBagger model in MATLAB? I’d like to know the best way to implement cross-validation in MATLAB with TreeBagger and whether there are specific functions or configurations that simplify this process. Could you provide guidance on using crossval or other methods to achieve cross-validation with TreeBagger for reliable performance evaluation?
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Answers (1)
Gayatri
on 8 Nov 2024 at 13:18
Hi Vedant,
You can apply cross-validation to TreeBagger using the 'crossval' function.
You can create a function for training a TreeBagger model and making predictions, as shown below:
function mpgMean = reg(X, Y, Xtest)
Mdl = TreeBagger(100, X, Y, 'Method', 'regression');
mpgMean = predict(Mdl, Xtest);
end
Then, you can use crossval on reg as follows:
>> mse = crossval('mse', XData, YData, 'Predfun', @reg, 'kfold', 10);
Please refer the following documentation for 'crossval' function: https://www.mathworks.com/help/stats/crossval.html
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