def predict(self, X):
        """
        Predict values using the model

        Parameters
        ----------
        X : {array-like, sparse matrix} of shape [n_samples, n_features]

        Returns
        -------
        C : numpy array of shape [n_samples, n_outputs]
            Predicted values.
        """
        if not self.fitted_:
            raise ValueError("ELMRegressor not fitted")

        # compute hidden layer activations
        self.hidden_activations_ = self.hidden_layer.transform(X)

        # compute output predictions for new hidden activations
        predictions = self._get_predictions()

        return predictions
Predict values using the model

        Parameters
        ----------
        X : {array-like, sparse matrix} of shape [n_samples, n_features]

        Returns
        -------
        C : numpy array of shape [n_samples, n_outputs]
            Predicted values.