parameters: (self, bin_thresholds=None)
return_statement: return TreePredictor(predictor_nodes)
docstring: Make a TreePredictor object out of the current tree.
  
          Parameters
          ----------
          bin_thresholds : array-like of floats, optional (default=None)
              The actual thresholds values of each bin.
  
          Returns
          -------
          A TreePredictor object.
docstring_summary: Make a TreePredictor object out of the current tree.
docstring_tokens: Make a TreePredictor object out of the current tree .
function: def make_predictor(self, bin_thresholds=None):
          """Make a TreePredictor object out of the current tree.
  
          Parameters
          ----------
          bin_thresholds : array-like of floats, optional (default=None)
              The actual thresholds values of each bin.
  
          Returns
          -------
          A TreePredictor object.
          """
          predictor_nodes = np.zeros(self.n_nodes, dtype=PREDICTOR_RECORD_DTYPE)
          _fill_predictor_node_array(predictor_nodes, self.root,
                                     bin_thresholds, self.n_bins_non_missing)
          return TreePredictor(predictor_nodes)
function_tokens: def make_predictor ( self , bin_thresholds = None ) : predictor_nodes = np . zeros ( self . n_nodes , dtype = PREDICTOR_RECORD_DTYPE ) _fill_predictor_node_array ( predictor_nodes , self . root , bin_thresholds , self . n_bins_non_missing ) return TreePredictor ( predictor_nodes )