docstr: The Total Within Cluster Sum-of-Square Error, or None if not present.
  
  :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.tot_withinss()
docstr_tok: ["The","Total","Within","Cluster","Sum-of-Square","Error",",","or","None","if","not","present",".",":","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.tot_withinss","(",")"]
code: def tot_withinss(self):
      """The Total Within Cluster Sum-of-Square Error, or None if not present.
  
      :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.tot_withinss()
      """
      if MetricsBase._has(self._metric_json, "tot_withinss"):
          return self._metric_json["tot_withinss"]
      return None
  
imports: import h2o
  from h2o.model import MetricsBase
label_desc: Use image node_id 2 for calling the H2OClusteringModelMetrics obj's underlying member method code with example usage: obj.tot_withinss() and returns: None, self