code: def HIST(**kwargs):
      """HIST class for Histogram based thresholders.
  
      Use histograms methods as described in scikit-image.filters to
      evaluate a non-parametric means to threshold scores generated by
      the decision_scores where outliers are set by histogram generated
      thresholds depending on the selected methods.
  
      Parameters
      ----------
  
      nbins : int, optional (default='auto')
           Number of bins to use in the hostogram, default set to int(len(scores)**0.7)
  
      method : {'otsu', 'yen', 'isodata', 'li', 'minimum', 'triangle'}, optional (default='triangle')
           Histogram filtering based method
  
           - 'otsu':     OTSU's method for filtering
           - 'yen':      Yen's method for filtering
           - 'isodata':  Ridler-Calvard or inter-means method for filtering
           - 'li':       Li's iterative Minimum Cross Entropy method for filtering
           - 'minimum':  Minimum between two maxima via smoothing method for filtering
           - 'triangle': Triangle algorithm method for filtering
      """
  
      from pythresh.thresholds.hist import HIST as HIST_thres
  
      return HIST_thres(**kwargs)
  
label_desc: Use image node_id 14 for calling a global function with example usage: HIST() and returns: HIST_thres