GridSearch for Ordinal Regression fails

[raviraju]

Used dataset (http://h2o-public-test-data.s3.amazonaws.com/bigdata/laptop/glm_ordinal_logit/ordinal_multinomial_training_set.csv) from tutorial to configure grid search

hyper_parameters = {'alpha': [0.01,0.3,0.5], 'lambda': [1e-5,1e-6,1e-7,1e-8]} gs = H2OGridSearch(H2OGeneralizedLinearEstimator(family='ordinal'), grid_id='ordinal_grid', hyper_params=hyper_parameters) gs.train(x=list(range(0,10)), y="C11", training_frame=train) gs.show()

glm Grid Build progress: |████████████████████████████████████100%

NotImplementedError Traceback (most recent call last) in () 4 grid_id='ordinal_grid', 5 hyper_params=hyper_parameters) ----> 6 gs.train(x=list(range(0,10)), y="C11", training_frame=train) 7 gs.show()

/apps/anaconda3/lib/python3.6/site-packages/h2o/grid/grid_search.py in train(self, x, y, training_frame, offset_column, fold_column, weights_column, validation_frame, **params) 206 x = list(xset) 207 parms["x"] = x --> 208 self.build_model(parms) 209 210

/apps/anaconda3/lib/python3.6/site-packages/h2o/grid/grid_search.py in build_model(self, algo_params) 221 if is_auto_encoder and y is not None: raise ValueError("y should not be specified for autoencoder.") 222 if not is_unsupervised and y is None: raise ValueError("Missing response") --> 223 self._model_build(x, y, training_frame, validation_frame, algo_params) 224 225

/apps/anaconda3/lib/python3.6/site-packages/h2o/grid/grid_search.py in _model_build(self, x, y, tframe, vframe, kwargs) 277 first_model_json = h2o.api("GET /%d/Models/%s" % 278 (rest_ver or 3, grid_json['model_ids'][0]['name']))['models'][0] --> 279 self._resolve_grid(grid.dest_key, grid_json, first_model_json) 280 else: 281 if len(failure_messages_stacks)>0:

/apps/anaconda3/lib/python3.6/site-packages/h2o/grid/grid_search.py in _resolve_grid(self, grid_id, grid_json, first_model_json) 286 287 def _resolve_grid(self, grid_id, grid_json, first_model_json): --> 288 model_class = H2OGridSearch._metrics_class(first_model_json) 289 m = model_class() 290 m._id = grid_id

/apps/anaconda3/lib/python3.6/site-packages/h2o/grid/grid_search.py in _metrics_class(model_json) 756 model_class = H2ODimReductionGridSearch 757 else: --> 758 raise NotImplementedError(model_type) 759 return model_class 760

NotImplementedError: Ordinal

[ABartzGit]

Hi, Ravi. You received the error because "family" is not a gridable parameter. Please see: http://docs.h2o.ai/h2o/latest-stable/h2o-docs/grid-search.html#glm-hyperparameters

Let me know if this helps and/or if you have any other questions. -Angela

[raviraju]

Hi Angela,

I understand "family" isn't a gridable parameter, however I have used it to instantiate GLM model for Ordinal Regression and have specified hyper_parameters dictionary for grid parameters.

I used example in https://github.com/h2oai/h2o-3/blob/master/h2o-docs/src/product/tutorials/random%20hyperparmeter%20search%20and%20roadmap.md#examples-Python for reference

[wendycwong]

Hi Ravi:

I fixed the problem for Python and added tests to make sure R also works. Here is the PR https://github.com/h2oai/h2o-3/pull/2429. Will push it into master as soon as it passed the test.

Thank you for catching it, Wendy

[wendycwong]

Merged into master.

[raviraju]

Hi Wendy,

Thanks for fix, Can u help me pull these changes using conda

[ABartzGit]

Hi Ravi, Thank you again for pointing out the bug. The fix is in the master branch and will be available on anaconda.org with the 3.20.0.1 release. You can test this in regular Python by downloading the nightly build: http://h2o-release.s3.amazonaws.com/h2o/master/4305/index.html.

Sincerely, Angela