code: def _fit_stacking_model(self,X, y, cost_mat, max_iter=100):
          
          self.f_staking = CostSensitiveLogisticRegression(verbose=self.verbose, max_iter=max_iter)
          X_stacking = _create_stacking_set(self.estimators_, self.estimators_features_,
                                            self.estimators_weight_, X, self.combination)
          self.f_staking.fit(X_stacking, y, cost_mat)
          return self
docs: Private function used to fit the stacking model.