sklearn.exceptions.FitFailedWarning

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.

Attributes
args

Examples

>>> 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.

Methods

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.