drf = H2ORandomForestEstimator(ntrees=5, max_depth=35 , weights_column="weights", nfolds=5, stopping_rounds=15, seed=55)

estimator = H2ORandomForestEstimator(weights_column="weights", nfolds=5, stopping_rounds=11, seed=55)

criteria = {
    "strategy": "RandomDiscrete",
    "stopping_tolerance": 0.001,
    "stopping_metric":"auc"
}

hyper_parameters = {
   'ntrees': [50, 100,200],
   'max_depth': [5, 10, 25, 50],
   'fold_assignment':['Stratified', 'Random']
}

gs = H2OGridSearch(estimator, hyper_params=hyper_parameters, search_criteria=criteria)

gs.train(x=predictors, y=response, training_frame=train_data, validation_frame=valid_data)


[OSError]: Job with key $03017f00000132d4ffffffff$_a07c1ae3a0a84dd4fa6dfc7a46904232 failed with an exception: java.lang.AssertionError: Cumulative capture rate must be 1.0, but is 0.9918032786885246