Converting H2O AutoML Model to Sklearn Model

Question

I have an H2O AutoML generated GBM model using python. I wonder if we can convert this into a standard sklearn model so that I can fit it into my ecosystem of other sklearn models. I can see the model properties as below when I print the model.

If direct conversion from H2O to sklearn is not feasible, is there a way we can use the above properties to recreate GBM in sklearn? These terminologies look slightly different from the standard sklearn GBM parameters.

Thanks in advance.

Answer 1

It will be a bit tricky, since the packages are a bit different. Sklearn is based on Python/Cython/C and H2O uses Java. The underlying algorithms could also be different. However, you can try matching/translating your hyperparameters between the two since they will be similar.

Additionally, it would be a good idea to have an ecosystem that is library agnostic so that you can interchange different models.