docstr: Retrieve the multinomial AUC values.
  
  :examples:
  
  >>> from h2o.estimators.gbm import H2OGradientBoostingEstimator
  >>> cars = h2o.import_file("https://s3.amazonaws.com/h2o-public-test-data/smalldata/junit/cars_20mpg.csv")
  >>> cars["cylinders"] = cars["cylinders"].asfactor()
  >>> train, valid = cars.split_frame(ratios=[.8], seed=1234)
  >>> response_col = "cylinders"
  >>> distribution = "multinomial"
  >>> predictors = ["displacement","power","weight","acceleration","year"]
  >>> gbm = H2OGradientBoostingEstimator(nfolds=3,
  ...                                    distribution = distribution)
  >>> gbm.train(x=predictors,
  ...           y = response,
  ...           training_frame = train,
  ...           validation_frame = valid)
  >>> gbm.multinomial_auc_table()
code: def multinomial_auc_table(self):
      """Retrieve the multinomial AUC values.
  
      :examples:
  
      >>> from h2o.estimators.gbm import H2OGradientBoostingEstimator
      >>> cars = h2o.import_file("https://s3.amazonaws.com/h2o-public-test-data/smalldata/junit/cars_20mpg.csv")
      >>> cars["cylinders"] = cars["cylinders"].asfactor()
      >>> train, valid = cars.split_frame(ratios=[.8], seed=1234)
      >>> response_col = "cylinders"
      >>> distribution = "multinomial"
      >>> predictors = ["displacement","power","weight","acceleration","year"]
      >>> gbm = H2OGradientBoostingEstimator(nfolds=3,
      ...                                    distribution = distribution)
      >>> gbm.train(x=predictors,
      ...           y = response,
      ...           training_frame = train,
      ...           validation_frame = valid)
      >>> gbm.multinomial_auc_table()
      """
      if self._metric_json["multinomial_auc_table"] is not None:
          return self._metric_json["multinomial_auc_table"]
      else:
          return (
              "AUC table was not computed: "
              "it is either disabled (model parameter 'auc_type' was set to AUTO or NONE) "
              "or the domain size exceeds the limit (maximum is 50 domains)."
          )
  
file_path: h2o-3/h2o-py/h2o/model/metrics/multinomial.py
imports: import h2o
  from h2o.model import MetricsBase
label_desc: Use image node_id 4 for calling the H2OMultinomialModelMetrics obj's underlying member method code with example usage: obj.multinomial_auc_table() and returns: self, str