class_docstr: AdaBoost
  
  Builds an AdaBoost model
class_docstr_tok: ["AdaBoost","Builds","an","AdaBoost","model"]
docstr: Choose a weak learner type. Defaults to AUTO, which means DRF.
  
  Type: ``Literal["auto", "drf", "glm", "gbm", "deep_learning"]``, defaults to ``"auto"``.
docstr_tok: ["Choose","a","weak","learner","type",".","Defaults","to","AUTO",",","which","means","DRF",".","Type",":","``","Literal","[","``","auto","''",",","``","drf","''",",","``","glm","''",",","``","gbm","''",",","``","deep_learning","''","]","``",",","defaults","to","``","``","auto","''","``","."]
code: def weak_learner(self):
      """
      Choose a weak learner type. Defaults to AUTO, which means DRF.
  
      Type: ``Literal["auto", "drf", "glm", "gbm", "deep_learning"]``, defaults to ``"auto"``.
      """
      return self._parms.get("weak_learner")
  
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 14 for calling the H2OAdaBoostEstimator obj's underlying member method code with example usage: obj.weak_learner() and returns: self