class_docstr: Jointly trains 2 surrogate decision trees.
  Refines diff (or sim) regions by sample generation.
code: def predict(self, x, tree):
      results = np.array([0] * len(x))
      for i, c in enumerate(x):
          # print(i,c)
          results[i] = self._get_prediction(c, tree)
      return results
  
imports: import numpy
  import pandas
  from aix360.algorithms.imd.rule import Rule
label_desc: Use image node_id 11 for calling the JointSurrogateTree obj's underlying member method code with example usage: obj.predict(x, tree) and returns: results