class_docstr: Analyze results of machine learning experiments.
docstr: Check if evaluator has evaluated any metrics.
docstr_tok: ["Check","if","evaluator","has","evaluated","any","metrics","."]
code: def _check_is_evaluated(self):
      """Check if evaluator has evaluated any metrics."""
      if len(self._metric_names) == 0:
          raise NotEvaluatedError(
              "This evaluator has not evaluated any metric yet. Please call "
              "'evaluate' with the appropriate arguments before using this "
              "method."
          )
  
imports: import itertools
  import numpy
  import pandas
  from scipy import stats
  from scipy.stats import ranksums, ttest_ind
  from sktime.benchmarking.base import BaseResults
  from sktime.exceptions import NotEvaluatedError
  from sktime.utils.validation._dependencies import _check_soft_dependencies
label_desc: Use image node_id 19 for calling the Evaluator obj's underlying member method code with example usage: obj._check_is_evaluated() without return types