H2O Generalized Linear Model for regression

This example shows how to build an H2O GLM model for regression, predict new data and score the regression metrics for model evaluation.

This is a companion discussion topic for the original entry at https://kni.me/w/FdAAnJjLcR0NjMPe

Hi, I can’t work out how to see the P-Values in the coefficients table - any ideas?

Also, the H2O documentation suggests you can fit interactions between variables but I can’t see any option in the configuration - is there a way of doing this that doesn’t involve Python or R?

Hi @marisamurton,

Since p-values are only provided by h2o for very restricted parameter settings (see documentation), we don’t output the p values a the moment.

This is currently not supported by the node. Just fyi, h2o computes the interactions on the fly if the parameter is not set. See https://docs.h2o.ai/h2o/latest-stable/h2o-docs/data-science/algo-params/interactions.html.


Thanks for replying Simon - I’m glad it wasn’t me being thick. The package I was used to for GLMs (Emblem) shows p values and allows easy fitting of interactions, they were useful features but alas the license fee is expensive…