class_docstr: Deepchecks Wrapper for the h2o autoML package.
docstr: Return the feature importances based on h2o internal calculation.
docstr_tok: ["Return","the","feature","importances","based","on","h2o","internal","calculation","."]
code: def feature_importances_(self) -> np.array:
      """Return the feature importances based on h2o internal calculation."""
      try:
          return self.model.varimp(use_pandas=True)["percentage"].values
      except:  # pylint: disable=bare-except # noqa
          return None
  
imports: import numpy
  import pandas
label_desc: Use image node_id 4 for calling the H2OWrapper obj's underlying member method code with example usage: obj.feature_importances_() and returns: self, None