I am using H2O's Python API to construct a GLM. To set the reference level for a categorical input I use relevel(). Based on the documentation it would seem as though relevel_by_frequency() would accomplish the same thing assuming I want the most frequency level as my base. What I find strange is that the GLM coefficient…
Has anyone had any luck producing lime values (tabular explainer) for an existing model and dataframe with mixed data types (categorical and continuous)? I've gone through tutorials and haven't had any luck getting values to be produced as the lime explainer expects data to be encoded and the model used data that wasn't…