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)
.