Predicts the values for the supplied data for each regressor in the CommitteeRegressor. Args: X: The samples to cast votes. **predict_kwargs: Keyword arguments to be passed to :meth:`predict` of the learners. Returns: The predicted value f
(self, X: modALinput, **predict_kwargs)
| 698 | return np.mean(vote, axis=1), np.std(vote, axis=1) |
| 699 | |
| 700 | def vote(self, X: modALinput, **predict_kwargs): |
| 701 | """ |
| 702 | Predicts the values for the supplied data for each regressor in the CommitteeRegressor. |
| 703 | Args: |
| 704 | X: The samples to cast votes. |
| 705 | **predict_kwargs: Keyword arguments to be passed to :meth:`predict` of the learners. |
| 706 | Returns: |
| 707 | The predicted value for each regressor in the CommitteeRegressor and each sample in X. |
| 708 | """ |
| 709 | prediction = np.zeros(shape=(len(X), len(self.learner_list))) |
| 710 | |
| 711 | for learner_idx, learner in enumerate(self.learner_list): |
| 712 | prediction[:, learner_idx] = learner.predict(X, **predict_kwargs).reshape(-1, ) |
| 713 | |
| 714 | return prediction |