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.

scoringstring, callable or None, optional, default: None

A string (see model evaluation documentation) or a scorer callable object / function with signature scorer(estimator, X, y).

allow_noneboolean, optional, 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).