class_docstr: Isolation Forest
  
  Builds an Isolation Forest model. Isolation Forest algorithm samples the training frame
  and in each iteration builds a tree that partitions the space of the sample observations until
  it isolates each observation. Length of the path from root to a leaf node of the resulting tree
  is used to calculate the anomaly score. Anomalies are easier to isolate and their average
  tree path is expected to be shorter than paths of regular observations.
class_docstr_tok: ["Isolation","Forest","Builds","an","Isolation","Forest","model",".","Isolation","Forest","algorithm","samples","the","training","frame","and","in","each","iteration","builds","a","tree","that","partitions","the","space","of","the","sample","observations","until","it","isolates","each","observation",".","Length","of","the","path","from","root","to","a","leaf","node","of","the","resulting","tree","is","used","to","calculate","the","anomaly","score",".","Anomalies","are","easier","to","isolate","and","their","average","tree","path","is","expected","to","be","shorter","than","paths","of","regular","observations","."]
code: def stopping_tolerance(self, stopping_tolerance):
      assert_is_type(stopping_tolerance, None, numeric)
      self._parms["stopping_tolerance"] = stopping_tolerance
  
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 41 for calling the H2OIsolationForestEstimator obj's underlying member method code with example usage: obj.stopping_tolerance(stopping_tolerance) without return types