class_docstr: AdaBoost
  
  Builds an AdaBoost model
class_docstr_tok: ["AdaBoost","Builds","an","AdaBoost","model"]
docstr: Customized parameters for the weak_learner algorithm.
  
  Type: ``dict``.
  
  :examples:
  
  >>> prostate_hex = h2o.import_file("http://s3.amazonaws.com/h2o-public-test-data/smalldata/prostate/prostate.csv")
  >>> prostate_hex["CAPSULE"] = prostate_hex["CAPSULE"].asfactor()
  >>> response = "CAPSULE"
  >>> seed = 42
  >>> adaboost_model = H2OAdaBoostEstimator(seed=seed,
  ...                                       weak_learner="DRF",
  ...                                       weak_learner_params={'ntrees':1,'max_depth':3})
  >>> adaboost_model.train(y=response,
  ...                 ignored_columns=["ID"],
  ...                 training_frame=prostate_hex)
  >>> print(adaboost_model)
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code: def weak_learner_params(self):
      """
      Customized parameters for the weak_learner algorithm.
  
      Type: ``dict``.
  
      :examples:
  
      >>> prostate_hex = h2o.import_file("http://s3.amazonaws.com/h2o-public-test-data/smalldata/prostate/prostate.csv")
      >>> prostate_hex["CAPSULE"] = prostate_hex["CAPSULE"].asfactor()
      >>> response = "CAPSULE"
      >>> seed = 42
      >>> adaboost_model = H2OAdaBoostEstimator(seed=seed,
      ...                                       weak_learner="DRF",
      ...                                       weak_learner_params={'ntrees':1,'max_depth':3})
      >>> adaboost_model.train(y=response,
      ...                 ignored_columns=["ID"],
      ...                 training_frame=prostate_hex)
      >>> print(adaboost_model)
      """
      if self._parms.get("weak_learner_params") != None:
          return json.loads(self._parms.get("weak_learner_params"))
      else:
          self._parms["weak_learner_params"] = None
  
imports: import ast
  import json
  from h2o.estimators.estimator_base import H2OEstimator
  from h2o.exceptions import H2OValueError
  from h2o.frame import H2OFrame
  from h2o.utils.typechecks import assert_is_type, Enum, numeric
  from h2o.estimators.estimator_base import H2OEstimator
  from h2o.exceptions import H2OValueError
  from h2o.frame import H2OFrame
  from h2o.utils.typechecks import assert_is_type, Enum, numeric
label_desc: Use image node_id 18 for calling the H2OAdaBoostEstimator obj's underlying member method code with example usage: obj.weak_learner_params() and returns: json