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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _fit_stacking_model(self,X, y, cost_mat, max_iter=100):
 """Private function used to fit the stacking model."""

        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