class_docstr: CaseEvaluationResults stores aggregated statistics for one EvaluationCase and one metric.
class_docstr_tok: ["CaseEvaluationResults","stores","aggregated","statistics","for","one","EvaluationCase","and","one","metric","."]
code: def __init__(self, case, metric_description, eval_step):
      self._case = case
      self._metric_description = metric_description
  
      self._fold_metric = pd.Series()
      self._fold_metric_iteration = pd.Series()
      self._fold_curves = dict()
  
      self._eval_step = eval_step
  
imports: import numpy
  import pandas
  from enum import Enum
  from ..None import CatBoostError
  from ..core import metric_description_or_str_to_str
  from ..utils import compute_wx_test
label_desc: Use image node_id 1 to create a new CaseEvaluationResult object  with example: obj = CaseEvaluationResult(case, metric_description, eval_step)