(self,
estimator: BaseEstimator,
query_strategy: Callable = uncertainty_sampling,
on_transformed: bool = False,
**fit_kwargs
)
| 202 | """ |
| 203 | |
| 204 | def __init__(self, |
| 205 | estimator: BaseEstimator, |
| 206 | query_strategy: Callable = uncertainty_sampling, |
| 207 | on_transformed: bool = False, |
| 208 | **fit_kwargs |
| 209 | ) -> None: |
| 210 | # TODO: Check if given query strategy works for Deep Learning |
| 211 | super().__init__(estimator, query_strategy, on_transformed, **fit_kwargs) |
| 212 | |
| 213 | self.estimator.initialize() |
| 214 | |
| 215 | def fit(self, X: modALinput, y: modALinput, bootstrap: bool = False, **fit_kwargs) -> 'BaseLearner': |
| 216 | """ |