MATLAB: How to determine the r-squared value for regression trees

r-squaredregression tree

I am using regression trees and I know that there is a way to determine an R^2 value for the tree, but I am not sure how to do it. I am using the function RegressionTree.fit with Matlab 2013a, but just downloaded 2014a on another computer. So I could use either version.

Best Answer

I don't think this is an output property of the model, but it is easy to calculate. Here is an example based on the one in the documentation for RegressionTree.fit:
load carsmall
tree = RegressionTree.fit([Weight, Cylinders],MPG,'MinParent',20,'PredictorNames',{'W','C'})
mpg_predicted = predict(tree,[Weight,Cylinders]);
RMSE = sqrt(nanmean((mpg_predicted-MPG).^2))
RMSE0 = nanstd(MPG-nanmean(MPG));
r_sq = 1 - (RMSE/RMSE0)
I would double-check all that, but you should be in the right direction.
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