Use the optimized pipeline to predict the target for a feature set.

        Parameters
        ----------
        features: array-like {n_samples, n_features}
            Feature matrix

        Returns
        ----------
        array-like: {n_samples}
            Predicted target for the samples in the feature matrix

def predict(self, features):
        """Use the optimized pipeline to predict the target for a feature set.

        Parameters
        ----------
        features: array-like {n_samples, n_features}
            Feature matrix

        Returns
        ----------
        array-like: {n_samples}
            Predicted target for the samples in the feature matrix

        """
        if not self.fitted_pipeline_:
            raise RuntimeError('A pipeline has not yet been optimized. Please call fit() first.')

        features = self._check_dataset(features, target=None, sample_weight=None)

        return self.fitted_pipeline_.predict(features)