def get_metric_value(self,
reset: bool = False
) -> Union[float, Dict[str, float]]:
if not self.is_initialized:
logger.warning(
"Trying to get not initialized metric, returning 0.")
return 0.0
mcm = self.multilabel_confusion_matrix
numerator = mcm[..., 1, 1]
denominator = mcm[..., 1, 1] + mcm[..., 1, 0]
precision = self._reduce_metric(numerator / denominator)
self._reset_if_needed(reset)
return precision
def get_metric_value(self,
reset: bool = False
) -> Union[float, Dict[str, float]]:
if not self.is_initialized:
logger.warning(
"Trying to get not initialized metric, returning 0.")
return 0.0
mcm = self.multilabel_confusion_matrix
tp_sum = mcm[:, 1, 1]
pred_sum = tp_sum + mcm[:, 0, 1]
true_sum = tp_sum + mcm[:, 1, 0]
precision = tp_sum / pred_sum
recall = tp_sum / true_sum
f_score = ((1 + self.beta2) * precision * recall /
(self.beta2 * precision + recall))
f_score = self._reduce_metric(f_score)
self._reset_if_needed(reset)
return f_score