2
votes

I am getting H2OResponseError: Server error water.exceptions.H2OIllegalArgumentException: Error: unimplemented

H2OResponseError: Server error water.exceptions.H2OIllegalArgumentException:
  Error: unimplemented
  Request: POST /3/PartialDependence/
    data: {'cols': '[offer_id]', 'model_id': 'GBM_grid__1_AutoML_20200510_220603_model_14', 'frame_id': 'digiq_wine_multiclass_training_1__scrubbed3.hex', 'nbins': '20', 'add_missing_na': 'False', 'row_index': '-1'}

When I try to find PDP for one of the datasets I am working with. This doesn't break for all the dataset but, in few peculiar cases like this one, it does. I am not able to find the reason, and not sure if this could be a bug of H2O. Having checked the log file, it shows the same error as above with no other relevant information. H2O_cluster_version: 3.30.0.1 Language: Python 3.7.6

I am providing the reproducible example pointing to my GitHub to readily see the visible error also can be downloaded and just run to experience it. I would appreciate it if anyone from the H2O team or relevant person to help in resolving or find the root cause of the issue. Thank you.

GitHub replicating example - https://github.com/prabhuSub/H2O-Water-Exception

Notebook in the repo - https://github.com/prabhuSub/H2O-Water-Exception/blob/master/Sample_issue.ipynb

logs - https://github.com/prabhuSub/H2O-Water-Exception/tree/master/h2ologs_node0_127.0.0.1_54321

The log file is added too for reference if required, for a quick investigation.

1

1 Answers

1
votes

Your dataset is called "digiq_wine_multiclass_training(1)_scrubbed.csv" so I assume you were have a multiclass classification problem? If so, then the reason you're hitting an error is because partial dependence plots are only implemented for regression or binary classification problems.