Interface for the fit method of the predictor. Fits the predictor to the supplied data, then stores it internally for the active learning loop. Args: X: The samples to be fitted. y: The corresponding labels. bootstrap: If true, trains the
(self, X: modALinput, y: modALinput, bootstrap: bool = False, **fit_kwargs)
| 134 | return self |
| 135 | |
| 136 | def fit(self, X: modALinput, y: modALinput, bootstrap: bool = False, **fit_kwargs) -> 'BaseLearner': |
| 137 | """ |
| 138 | Interface for the fit method of the predictor. Fits the predictor to the supplied data, then stores it |
| 139 | internally for the active learning loop. |
| 140 | |
| 141 | Args: |
| 142 | X: The samples to be fitted. |
| 143 | y: The corresponding labels. |
| 144 | bootstrap: If true, trains the estimator on a set bootstrapped from X. |
| 145 | Useful for building Committee models with bagging. |
| 146 | **fit_kwargs: Keyword arguments to be passed to the fit method of the predictor. |
| 147 | |
| 148 | Note: |
| 149 | When using scikit-learn estimators, calling this method will make the ActiveLearner forget all training data |
| 150 | it has seen! |
| 151 | |
| 152 | Returns: |
| 153 | self |
| 154 | """ |
| 155 | check_X_y(X, y, accept_sparse=True, ensure_2d=False, allow_nd=True, multi_output=True, dtype=None, |
| 156 | force_all_finite=self.force_all_finite) |
| 157 | self.X_training, self.y_training = X, y |
| 158 | return self._fit_to_known(bootstrap=bootstrap, **fit_kwargs) |
| 159 | |
| 160 | def teach(self, X: modALinput, y: modALinput, bootstrap: bool = False, only_new: bool = False, **fit_kwargs) -> None: |
| 161 | """ |