Returns the mean accuracy on the given test data and labels. Todo: Why accuracy? Args: X: The samples to score. y: Ground truth labels corresponding to X. sample_weight: Sample weights. Returns: Mean accurac
(self, X: modALinput, y: modALinput, sample_weight: List[float] = None)
| 565 | return np.mean(self.vote_proba(X, **predict_proba_kwargs), axis=1) |
| 566 | |
| 567 | def score(self, X: modALinput, y: modALinput, sample_weight: List[float] = None) -> Any: |
| 568 | """ |
| 569 | Returns the mean accuracy on the given test data and labels. |
| 570 | Todo: |
| 571 | Why accuracy? |
| 572 | Args: |
| 573 | X: The samples to score. |
| 574 | y: Ground truth labels corresponding to X. |
| 575 | sample_weight: Sample weights. |
| 576 | Returns: |
| 577 | Mean accuracy of the classifiers. |
| 578 | """ |
| 579 | y_pred = self.predict(X) |
| 580 | return accuracy_score(y, y_pred, sample_weight=sample_weight) |
| 581 | |
| 582 | def vote(self, X: modALinput, **predict_kwargs) -> Any: |
| 583 | """ |