Interface for the fit method of the predictor. Fits the predictor to the supplied data. Args: X: The samples to be fitted. y: The corresponding labels. bootstrap: If true, trains the estimator on a set bootstrapped from X. Useful
(self, X: modALinput, y: modALinput, bootstrap: bool = False, **fit_kwargs)
| 213 | self.estimator.initialize() |
| 214 | |
| 215 | def fit(self, X: modALinput, y: modALinput, bootstrap: bool = False, **fit_kwargs) -> 'BaseLearner': |
| 216 | """ |
| 217 | Interface for the fit method of the predictor. Fits the predictor to the supplied data. |
| 218 | |
| 219 | Args: |
| 220 | X: The samples to be fitted. |
| 221 | y: The corresponding labels. |
| 222 | bootstrap: If true, trains the estimator on a set bootstrapped from X. |
| 223 | Useful for building Committee models with bagging. |
| 224 | **fit_kwargs: Keyword arguments to be passed to the fit method of the predictor. |
| 225 | |
| 226 | Returns: |
| 227 | self |
| 228 | """ |
| 229 | return self._fit_on_new(X, y, bootstrap=bootstrap, **fit_kwargs) |
| 230 | |
| 231 | def teach(self, X: modALinput, y: modALinput, warm_start: bool = True, bootstrap: bool = False, **fit_kwargs) -> None: |
| 232 | """ |
nothing calls this directly
no test coverage detected