class_docstr: Singular Value Decomposition
docstr: Id of the training data frame.
  
  Type: ``Union[None, str, H2OFrame]``.
  
  :examples:
  
  >>> arrests = h2o.import_file("https://s3.amazonaws.com/h2o-public-test-data/smalldata/pca_test/USArrests.csv")
  >>> fit_h2o = H2OSingularValueDecompositionEstimator()
  >>> fit_h2o.train(x=list(range(4)), training_frame=arrests)
  >>> fit_h2o
docstr_tok: ["Id","of","the","training","data","frame",".","Type",":","``","Union","[","None",",","str",",","H2OFrame","]","``",".",":","examples",":",">",">",">","arrests","=","h2o.import_file","(","``","https",":","\/\/s3.amazonaws.com\/h2o-public-test-data\/smalldata\/pca_test\/USArrests.csv","''",")",">",">",">","fit_h2o","=","H2OSingularValueDecompositionEstimator","(",")",">",">",">","fit_h2o.train","(","x=list","(","range","(","4",")",")",",","training_frame=arrests",")",">",">",">","fit_h2o"]
code: def training_frame(self):
      """
      Id of the training data frame.
  
      Type: ``Union[None, str, H2OFrame]``.
  
      :examples:
  
      >>> arrests = h2o.import_file("https://s3.amazonaws.com/h2o-public-test-data/smalldata/pca_test/USArrests.csv")
      >>> fit_h2o = H2OSingularValueDecompositionEstimator()
      >>> fit_h2o.train(x=list(range(4)), training_frame=arrests)
      >>> fit_h2o
      """
      return self._parms.get("training_frame")
  
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 2 for calling the H2OSingularValueDecompositionEstimator obj's underlying member method code with example usage: obj.training_frame() and returns: self