sklearn.metrics.check_scoring¶
- 
sklearn.metrics.check_scoring(estimator, scoring=None, *, allow_none=False)[source]¶
- Determine scorer from user options. - A TypeError will be thrown if the estimator cannot be scored. - Parameters
- estimatorestimator object implementing ‘fit’
- The object to use to fit the data. 
- scoringstr or callable, default=None
- A string (see model evaluation documentation) or a scorer callable object / function with signature - scorer(estimator, X, y).
- allow_nonebool, default=False
- If no scoring is specified and the estimator has no score function, we can either return None or raise an exception. 
 
- Returns
- scoringcallable
- A scorer callable object / function with signature - scorer(estimator, X, y).
 
 
