class_docstr: Analyze results of machine learning experiments.
code: def __init__(self, results):
      if not isinstance(results, BaseResults):
          raise ValueError("`results` must inherit from BaseResults")
      self.results = results
      self._metric_dicts = []
  
      # preallocate dataframe for metrics
      self._metrics = pd.DataFrame(
          columns=["dataset", "strategy", "cv_fold"]
      )
      self._metrics_by_strategy_dataset = pd.DataFrame(
          columns=["dataset", "strategy"]
      )
      self._metrics_by_strategy = pd.DataFrame(columns=["strategy"])
  
      # keep track of metric names
      self._metric_names = []
  
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 1 to create a new Evaluator object  with example: obj = Evaluator(results)