sklearn.metrics.check_scoring — scikit-learn 0.20.4 documentation (original) (raw)

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:	estimator : estimator object implementing ‘fit’ The object to use to fit the data. scoring : string, callable or None, optional, default: None A string (see model evaluation documentation) or a scorer callable object / function with signaturescorer(estimator, X, y). allow_none : boolean, 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:	scoring : callable A scorer callable object / function with signaturescorer(estimator, X, y).

Parameters:

estimator : estimator object implementing ‘fit’ The object to use to fit the data. scoring : string, callable or None, optional, default: None A string (see model evaluation documentation) or a scorer callable object / function with signaturescorer(estimator, X, y). allow_none : boolean, 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:

scoring : callable A scorer callable object / function with signaturescorer(estimator, X, y).