You have just trained a gradient boosting machine (GBM) and a random forest (RF) classifier on your data using Stata’s new h2oml command suite. Your GBM model achieves 87% accuracy on the testing data, and your RF model, 85%. It looks as if GBM is the preferred classifier, right? Not so fast.
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