'Returns an (accuracy, precision, recall, F1-score)-tuple for the given documents,
with values between 0.0 and 1.0 (0-100%).
Accuracy is the percentage of correct predictions for the given test set,
but this metric can be misleading (e.g., classifier *always* predicts True).
Precision is the percentage of predictions that were correct.
Recall is the percentage of documents that were correctly labeled.
F1-score is the harmonic mean of precision and recall.'

def _test(self, documents=[], target=None, **kwargs):

    return self.confusion_matrix(documents).test(target)
