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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 coef_(self):
 """Return the aggregated coefficients. Returns ------- coef_ : ndarray, shape = (n_features + 1,) Coefficients of features. The first element denotes the intercept. """

        coef = numpy.zeros(self.n_features_ + 1, dtype=float)

        for estimator in self.estimators_:
            coef[estimator.component] += self.learning_rate * estimator.coef_

        return coef