class sklearn.exceptions.FitFailedWarning
[source]
Warning class used if there is an error while fitting the estimator.
This Warning is used in meta estimators GridSearchCV and RandomizedSearchCV and the cross-validation helper function cross_val_score to warn when there is an error while fitting the estimator.
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>>> from sklearn.model_selection import GridSearchCV >>> from sklearn.svm import LinearSVC >>> from sklearn.exceptions import FitFailedWarning >>> import warnings >>> warnings.simplefilter('always', FitFailedWarning) >>> gs = GridSearchCV(LinearSVC(), {'C': [-1, -2]}, error_score=0, cv=2) >>> X, y = [[1, 2], [3, 4], [5, 6], [7, 8]], [0, 0, 1, 1] >>> with warnings.catch_warnings(record=True) as w: ... try: ... gs.fit(X, y) # This will raise a ValueError since C is < 0 ... except ValueError: ... pass ... print(repr(w[-1].message)) ... FitFailedWarning('Estimator fit failed. The score on this train-test partition for these parameters will be set to 0.000000. Details: \nValueError: Penalty term must be positive; got (C=-2)\n'...)
Changed in version 0.18: Moved from sklearn.cross_validation.
with_traceback | Exception.with_traceback(tb) – set self.__traceback__ to tb and return self. |
with_traceback()
Exception.with_traceback(tb) – set self.__traceback__ to tb and return self.
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Licensed under the 3-clause BSD License.
http://scikit-learn.org/stable/modules/generated/sklearn.exceptions.FitFailedWarning.html