code: def precision_wilson(y_true, y_pred):
      assert len(y_true) == len(y_pred)
      tn, fp, fn, tp = confusion_matrix(y_true, y_pred).ravel()
      return general_cm_wilson(tp, fp, digits_of_precision, z_score)
  
file_path: responsible-ai-toolbox/raiwidgets/raiwidgets/fairness_metric_calculation.py
imports: import importlib
  import numpy
  from packaging import version
  from sklearn.metrics import confusion_matrix
label_desc: Use image node_id 5 for calling a global function with example usage: precision_wilson(y_true, y_pred) and returns: general_cm_wilson