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exceptions.cpython-35.opt-1.pyc
��(XQ � @ s� d Z d d d d d d d d d g Z Gd d � d e e � Z Gd d � d e � Z Gd d � d e � Z Gd d � d e � Z Gd d � d e � Z Gd d � d e � Z Gd d � d e � Z Gd d � d e � Z Gd d � d e � Z d S)zo The :mod:`sklearn.exceptions` module includes all custom warnings and error classes used across scikit-learn. �NotFittedError�ChangedBehaviorWarning�ConvergenceWarning�DataConversionWarning�DataDimensionalityWarning�EfficiencyWarning�FitFailedWarning�NonBLASDotWarning�UndefinedMetricWarningc @ s e Z d Z d Z d S)r a� Exception class to raise if estimator is used before fitting. This class inherits from both ValueError and AttributeError to help with exception handling and backward compatibility. Examples -------- >>> from sklearn.svm import LinearSVC >>> from sklearn.exceptions import NotFittedError >>> try: ... LinearSVC().predict([[1, 2], [2, 3], [3, 4]]) ... except NotFittedError as e: ... print(repr(e)) ... # doctest: +NORMALIZE_WHITESPACE +ELLIPSIS NotFittedError('This LinearSVC instance is not fitted yet',) .. versionchanged:: 0.18 Moved from sklearn.utils.validation. N)�__name__� __module__�__qualname__�__doc__� r r �/exceptions.pyr s c @ s e Z d Z d Z d S)r z�Warning class used to notify the user of any change in the behavior. .. versionchanged:: 0.18 Moved from sklearn.base. N)r r r r r r r r r '