class_docstr: Cox Proportional Hazards
  
  Trains a Cox Proportional Hazards Model (CoxPH) on an H2O dataset.
class_docstr_tok: ["Cox","Proportional","Hazards","Trains","a","Cox","Proportional","Hazards","Model","(","CoxPH",")","on","an","H2O","dataset","."]
docstr: Automatically export generated models to this directory.
  
  Type: ``str``.
  
  :examples:
  
  >>> import tempfile
  >>> from os import listdir
  >>> heart = h2o.import_file("http://s3.amazonaws.com/h2o-public-test-data/smalldata/coxph_test/heart.csv")
  >>> predictor = "age"
  >>> response = "event"
  >>> checkpoints_dir = tempfile.mkdtemp()
  >>> coxph = H2OCoxProportionalHazardsEstimator(start_column="start",
  ...                                            stop_column="stop",
  ...                                            export_checkpoints_dir=checkpoints_dir)
  >>> coxph.train(x=predictor,
  ...             y=response,
  ...             training_frame=heart)
  >>> len(listdir(checkpoints_dir))
docstr_tok: ["Automatically","export","generated","models","to","this","directory",".","Type",":","``","str","``",".",":","examples",":",">",">",">","import","tempfile",">",">",">","from","os","import","listdir",">",">",">","heart","=","h2o.import_file","(","``","http",":","\/\/s3.amazonaws.com\/h2o-public-test-data\/smalldata\/coxph_test\/heart.csv","''",")",">",">",">","predictor","=","``","age","''",">",">",">","response","=","``","event","''",">",">",">","checkpoints_dir","=","tempfile.mkdtemp","(",")",">",">",">","coxph","=","H2OCoxProportionalHazardsEstimator","(","start_column=","''","start","''",",","...","stop_column=","''","stop","''",",","...","export_checkpoints_dir=checkpoints_dir",")",">",">",">","coxph.train","(","x=predictor",",","...","y=response",",","...","training_frame=heart",")",">",">",">","len","(","listdir","(","checkpoints_dir",")",")"]
code: def export_checkpoints_dir(self):
      """
      Automatically export generated models to this directory.
  
      Type: ``str``.
  
      :examples:
  
      >>> import tempfile
      >>> from os import listdir
      >>> heart = h2o.import_file("http://s3.amazonaws.com/h2o-public-test-data/smalldata/coxph_test/heart.csv")
      >>> predictor = "age"
      >>> response = "event"
      >>> checkpoints_dir = tempfile.mkdtemp()
      >>> coxph = H2OCoxProportionalHazardsEstimator(start_column="start",
      ...                                            stop_column="stop",
      ...                                            export_checkpoints_dir=checkpoints_dir)
      >>> coxph.train(x=predictor,
      ...             y=response,
      ...             training_frame=heart)
      >>> len(listdir(checkpoints_dir))
      """
      return self._parms.get("export_checkpoints_dir")
  
imports: 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 34 for calling the H2OCoxProportionalHazardsEstimator obj's underlying member method code with example usage: obj.export_checkpoints_dir() and returns: self