def evaluate(self, text):
"""
Given a string of `text`, compute confusion matrix for the
classification task.
"""
cx = BinaryConfusion()
for (L, P, R, gold, _) in self.candidates(text):
guess = self.predict(L, P, R)
cx.update(gold, guess)
if not gold and guess:
logging.debug("False pos.: L='{}', R='{}'.".format(L, R))
elif gold and not guess:
logging.debug("False neg.: L='{}', R='{}'.".format(L, R))
return cx
def evaluate(self, text):
"""
Given a string of `text`, compute confusion matrix for the
classification task.
"""
cx = BinaryConfusion()
for (L, P, R, gold, _) in Detector.candidates(text):
guess = self.predict(L, P, R)
cx.update(gold, guess)
if not gold and guess:
logging.debug("False pos.: L='{}', R='{}'.".format(L, R))
elif gold and not guess:
logging.debug("False neg.: L='{}', R='{}'.".format(L, R))
return cx