docstr: Retrieve the Hit Ratios.
  
  If all are ``False`` (default), then return the training metric value.
  If more than one options is set to ``True``, then return a dictionary of metrics where the keys are "train",
  "valid", and "xval".
  
  :param train: If train is ``True``, then return the hit ratio value for the training data.
  :param valid: If valid is ``True``, then return the hit ratio value for the validation data.
  :param xval:  If xval is ``True``, then return the hit ratio value for the cross validation data.
  :return: The hit ratio for this regression model.
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code: def hit_ratio_table(self, train=False, valid=False, xval=False):
      """
      Retrieve the Hit Ratios.
  
      If all are ``False`` (default), then return the training metric value.
      If more than one options is set to ``True``, then return a dictionary of metrics where the keys are "train",
      "valid", and "xval".
  
      :param train: If train is ``True``, then return the hit ratio value for the training data.
      :param valid: If valid is ``True``, then return the hit ratio value for the validation data.
      :param xval:  If xval is ``True``, then return the hit ratio value for the cross validation data.
      :return: The hit ratio for this regression model.
      """
      tm = ModelBase._get_metrics(self, train, valid, xval)
      m = {}
      for k, v in zip(list(tm.keys()), list(tm.values())):
          m[k] = None if v is None else v.hit_ratio_table()
      return list(m.values())[0] if len(m) == 1 else m
  
file_path: h2o-3/h2o-py/h2o/model/models/ordinal.py
imports: import h2o
  from h2o.exceptions import H2OValueError
  from h2o.frame import H2OFrame
  from h2o.model import ModelBase
  from h2o.model.extensions import has_extension
  from h2o.utils.compatibility import *
  from h2o.utils.typechecks import assert_is_type
label_desc: Use image node_id 2 for calling the H2OOrdinalModel obj's underlying member method code with example usage: obj.hit_ratio_table(train, valid, xval) and returns: unknown