class_docstr: TargetEncoder
docstr: Inflection point of the sigmoid used to blend probabilities (see `blending` parameter). For a given categorical
  value, if it appears less that `inflection_point` in a data sample, then the influence of the posterior
  probability will be smaller than the prior.
  
  Type: ``float``, defaults to ``10.0``.
  
  :examples:
  
  >>> titanic = h2o.import_file("https://s3.amazonaws.com/h2o-public-test-data/smalldata/gbm_test/titanic.csv")
  >>> predictors = ["home.dest", "cabin", "embarked"]
  >>> response = "survived"
  >>> titanic["survived"] = titanic["survived"].asfactor()
  >>> fold_col = "kfold_column"
  >>> titanic[fold_col] = titanic.kfold_column(n_folds=5, seed=1234)
  >>> titanic_te = H2OTargetEncoderEstimator(inflection_point=35,
  ...                                        smoothing=25,
  ...                                        blending=True)
  >>> titanic_te.train(x=predictors,
  ...                  y=response,
  ...                  training_frame=titanic)
  >>> titanic_te
docstr_tok: ["Inflection","point","of","the","sigmoid","used","to","blend","probabilities","(","see","`","blending","`","parameter",")",".","For","a","given","categorical","value",",","if","it","appears","less","that","`","inflection_point","`","in","a","data","sample",",","then","the","influence","of","the","posterior","probability","will","be","smaller","than","the","prior",".","Type",":","``","float","``",",","defaults","to","``","10.0","``",".",":","examples",":",">",">",">","titanic","=","h2o.import_file","(","``","https",":","\/\/s3.amazonaws.com\/h2o-public-test-data\/smalldata\/gbm_test\/titanic.csv","''",")",">",">",">","predictors","=","[","``","home.dest","''",",","``","cabin","''",",","``","embarked","''","]",">",">",">","response","=","``","survived","''",">",">",">","titanic","[","``","survived","''","]","=","titanic","[","``","survived","''","]",".asfactor","(",")",">",">",">","fold_col","=","``","kfold_column","''",">",">",">","titanic","[","fold_col","]","=","titanic.kfold_column","(","n_folds=5",",","seed=1234",")",">",">",">","titanic_te","=","H2OTargetEncoderEstimator","(","inflection_point=35",",","...","smoothing=25",",","...","blending=True",")",">",">",">","titanic_te.train","(","x=predictors",",","...","y=response",",","...","training_frame=titanic",")",">",">",">","titanic_te"]
code: def inflection_point(self):
      """
      Inflection point of the sigmoid used to blend probabilities (see `blending` parameter). For a given categorical
      value, if it appears less that `inflection_point` in a data sample, then the influence of the posterior
      probability will be smaller than the prior.
  
      Type: ``float``, defaults to ``10.0``.
  
      :examples:
  
      >>> titanic = h2o.import_file("https://s3.amazonaws.com/h2o-public-test-data/smalldata/gbm_test/titanic.csv")
      >>> predictors = ["home.dest", "cabin", "embarked"]
      >>> response = "survived"
      >>> titanic["survived"] = titanic["survived"].asfactor()
      >>> fold_col = "kfold_column"
      >>> titanic[fold_col] = titanic.kfold_column(n_folds=5, seed=1234)
      >>> titanic_te = H2OTargetEncoderEstimator(inflection_point=35,
      ...                                        smoothing=25,
      ...                                        blending=True)
      >>> titanic_te.train(x=predictors,
      ...                  y=response,
      ...                  training_frame=titanic)
      >>> titanic_te
      """
      return self._parms.get("inflection_point")
  
imports: from h2o.utils.metaclass import deprecated_params, deprecated_property
  import h2o
  import warnings
  from h2o.exceptions import H2ODeprecationWarning
  from h2o.utils.typechecks import U
  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 16 for calling the H2OTargetEncoderEstimator obj's underlying member method code with example usage: obj.inflection_point() and returns: self