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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 _find_errors_param(self):
 """ Searches for the parameter on the estimator that contains the array of errors that was used to determine the optimal alpha. If it cannot find the parameter then a YellowbrickValueError is raised. """


        # NOTE: The order of the search is very important!
        if hasattr(self.estimator, 'mse_path_'):
            return self.estimator.mse_path_.mean(1)

        if hasattr(self.estimator, 'cv_values_'):
            return self.estimator.cv_values_.mean(0)

        raise YellowbrickValueError(
            "could not find errors param on {} estimator".format(
                self.estimator.__class__.__name__
            )
        )