class_docstr: evaluation result class for binary classification problem
class_docstr_tok: ["evaluation","result","class","for","binary","classification","problem"]
docstr: save metrics into the object result class
  
  Args:
      evaluation_result(dict): key-value pair for metric
          - key: metric name
          - value: metric dict
      label(list): classification label list
docstr_tok: ["save","metrics","into","the","object","result","class","Args",":","evaluation_result","(","dict",")",":","key-value","pair","for","metric","-","key",":","metric","name","-","value",":","metric","dict","label","(","list",")",":","classification","label","list"]
code: def load_results_from_meta(
      self, evaluation_result: dict, label: List = None
  ):
      """
      save metrics into the object result class
  
      Args:
          evaluation_result(dict): key-value pair for metric
              - key: metric name
              - value: metric dict
          label(list): classification label list
      """
      for metric, value in evaluation_result.items():
          if metric == constants.METRIC_CM:
              if label is None:
                  label = ["0", "1"]
              self.confusion_matrix = ConfusionMatrix(
                  label=label, confusion_matrix=value
              )
          else:
              self.update_result(metric, 1, value)
  
file_path: contextual-ai/xai/model/evaluation/binary_classification_result.py
imports: from typing import List
  from xai import constants
  from xai.model.evaluation.basic_result import ClassificationResult
  from xai.model.evaluation.confusion_matrix import ConfusionMatrix
  from xai.util import get_table_layout
label_desc: Use image node_id 2 for calling the BinaryClassificationResult obj's underlying member method code with example usage: obj.load_results_from_meta(evaluation_result, label) without return types