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:

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 signature scorer(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 signature scorer(estimator, X, y).