code: def interpret_data(X, y, func):
      explainer = LimeTabularExplainer(
          X, discretize_continuous=False, kernel_width=3
      )
      times, scores = [], []
      for r_idx in range(100):
          start_time = time.time()
          explanation = explainer.explain_instance(X[r_idx, :], func)
          times.append(time.time() - start_time)
          scores.append(explanation.score)
          print("...")
  
      return times, scores
  
imports: import time
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.datasets import make_classification
  from lime.lime_tabular import LimeTabularExplainer
label_desc: Use image node_id 1 for calling a global function with example usage: interpret_data(X, y, func) and returns: times,  scores