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Now sets classes when fitting committee #100

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Sep 22, 2020
Merged

Now sets classes when fitting committee #100

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17 changes: 16 additions & 1 deletion modAL/models/learners.py
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Original file line number Diff line number Diff line change
Expand Up @@ -312,6 +312,22 @@ def _set_classes(self):
def _add_training_data(self, X: modALinput, y: modALinput):
super()._add_training_data(X, y)

def fit(self, X: modALinput, y: modALinput, **fit_kwargs) -> 'BaseCommittee':
"""
Fits every learner to a subset sampled with replacement from X. Calling this method makes the learner forget the
data it has seen up until this point and replaces it with X! If you would like to perform bootstrapping on each
learner using the data it has seen, use the method .rebag()!

Calling this method makes the learner forget the data it has seen up until this point and replaces it with X!

Args:
X: The samples to be fitted on.
y: The corresponding labels.
**fit_kwargs: Keyword arguments to be passed to the fit method of the predictor.
"""
super().fit(X, y, **fit_kwargs)
self._set_classes()

def teach(self, X: modALinput, y: modALinput, bootstrap: bool = False, only_new: bool = False, **fit_kwargs) -> None:
"""
Adds X and y to the known training data for each learner and retrains learners with the augmented dataset.
Expand All @@ -323,7 +339,6 @@ def teach(self, X: modALinput, y: modALinput, bootstrap: bool = False, only_new:
only_new: If True, the model is retrained using only X and y, ignoring the previously provided examples.
**fit_kwargs: Keyword arguments to be passed to the fit method of the predictor.
"""

super().teach(X, y, bootstrap=bootstrap, only_new=only_new, **fit_kwargs)
self._set_classes()

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