docstr: Get the number of iterations it took to converge or reach max iterations.
  
  :examples:
  
  >>> from h2o.estimators.kmeans import H2OKMeansEstimator
  >>>
  >>> iris = h2o.import_file("https://s3.amazonaws.com/h2o-public-test-data/smalldata/iris/iris_train.csv")
  >>> km = H2OKMeansEstimator(k=3, nfolds=3)
  >>> km.train(x=list(range(4)), training_frame=iris)
  >>> km.num_iterations()
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code: def num_iterations(self):
      """Get the number of iterations it took to converge or reach max iterations.
  
      :examples:
  
      >>> from h2o.estimators.kmeans import H2OKMeansEstimator
      >>>
      >>> iris = h2o.import_file("https://s3.amazonaws.com/h2o-public-test-data/smalldata/iris/iris_train.csv")
      >>> km = H2OKMeansEstimator(k=3, nfolds=3)
      >>> km.train(x=list(range(4)), training_frame=iris)
      >>> km.num_iterations()
      """
      o = self._model_json["output"]
      return o["model_summary"]["number_of_iterations"][0]
  
file_path: h2o-3/h2o-py/h2o/model/models/clustering.py
imports: from h2o.utils.compatibility import *
  from h2o.model import ModelBase
label_desc: Use image node_id 2 for calling the H2OClusteringModel obj's underlying member method code with example usage: obj.num_iterations() and returns: o