class_docstr: Class for explanation aggregator. It aggregates the explanations based on classes, feature and scores.
code: def __init__(self, confidence_threshold=0.8):
      self._explanation_list = defaultdict(list)
      self._total_count = 0
      self._class_counter = defaultdict(int)
      self._confidence_threshold = confidence_threshold
  
file_path: contextual-ai/xai/model/interpreter/explanation_aggregator.py
imports: import operator
  from collections import defaultdict, Counter
  from typing import Dict, Tuple, List, Set
  from xai.explainer.constants import OUTPUT
  from xai.model.interpreter.exceptions import InvalidExplanationFormat, MutipleScoresFoundForSameFeature, UnsupportedMethodType, InvalidArgumentError
label_desc: Use image node_id 1 to create a new ExplanationAggregator object  with example: obj = ExplanationAggregator(confidence_threshold)