code: def _reverse_window_score_gain(masks, order, start, length):
      forward_score = _mask_delta_score(
          masks[order[start - 1]], masks[order[start]]
      ) + _mask_delta_score(
          masks[order[start + length - 1]], masks[order[start + length]]
      )
      reverse_score = _mask_delta_score(
          masks[order[start - 1]], masks[order[start + length - 1]]
      ) + _mask_delta_score(
          masks[order[start]], masks[order[start + length]]
      )
  
      return forward_score - reverse_score
  
file_path: shap/shap/utils/_clustering.py
imports: import warnings
  import numpy
  import pandas
  import scipy.cluster
  import scipy.spatial
  import sklearn
  from numba import njit
  from ._show_progress import show_progress
label_desc: Use image node_id 6 for calling a global function with example usage: _reverse_window_score_gain(masks, order, start, length) and returns: unknown