class_docstr: Singular Value Decomposition
docstr: Method for computing SVD (Caution: Randomized is currently experimental and unstable)
  
  Type: ``Literal["gram_s_v_d", "power", "randomized"]``, defaults to ``"gram_s_v_d"``.
  
  :examples:
  
  >>> arrests = h2o.import_file("https://s3.amazonaws.com/h2o-public-test-data/smalldata/pca_test/USArrests.csv")
  >>> fit_h2o = H2OSingularValueDecompositionEstimator(svd_method="power")
  >>> fit_h2o.train(x=list(range(4)), training_frame=arrests)
  >>> fit_h2o
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code: def svd_method(self):
      """
      Method for computing SVD (Caution: Randomized is currently experimental and unstable)
  
      Type: ``Literal["gram_s_v_d", "power", "randomized"]``, defaults to ``"gram_s_v_d"``.
  
      :examples:
  
      >>> arrests = h2o.import_file("https://s3.amazonaws.com/h2o-public-test-data/smalldata/pca_test/USArrests.csv")
      >>> fit_h2o = H2OSingularValueDecompositionEstimator(svd_method="power")
      >>> fit_h2o.train(x=list(range(4)), training_frame=arrests)
      >>> fit_h2o
      """
      return self._parms.get("svd_method")
  
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 14 for calling the H2OSingularValueDecompositionEstimator obj's underlying member method code with example usage: obj.svd_method() and returns: self