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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 predict(self, testing_features):
 """predict on a holdout data set."""

        # print("best_inds:",self._best_inds)
        # print("best estimator size:",self._best_estimator.coef_.shape)
        if self.clean:
            testing_features = self.impute_data(testing_features)

        if self._best_inds:
            X_transform = self.transform(testing_features)
            try:
                return self._best_estimator.predict(self.transform(testing_features))
            except ValueError as detail:
                # pdb.set_trace()
                print('shape of X:',testing_features.shape)
                print('shape of X_transform:',X_transform.transpose().shape)
                print('best inds:',self.stacks_2_eqns(self._best_inds))
                print('valid locs:',self.valid_loc(self._best_inds))
                raise ValueError(detail)
        else:
            return self._best_estimator.predict(testing_features)