[GitHub] [incubator-mxnet] sxjscience commented on a change in pull request #18083: Changes to mxnet.metric

[GitBox <gi...@apache.org>]

sxjscience commented on a change in pull request #18083: Changes to mxnet.metric
URL: https://github.com/apache/incubator-mxnet/pull/18083#discussion_r409657973
 
 

 ##########
 File path: python/mxnet/gluon/metric.py
 ##########
 @@ -777,16 +815,113 @@ class F1(EvalMetric):
     --------
     >>> predicts = [mx.nd.array([[0.3, 0.7], [0., 1.], [0.4, 0.6]])]
     >>> labels   = [mx.nd.array([0., 1., 1.])]
-    >>> f1 = mx.metric.F1()
+    >>> f1 = mx.gluon.metric.F1()
     >>> f1.update(preds = predicts, labels = labels)
     >>> print f1.get()
     ('f1', 0.8)
     """
 
     def __init__(self, name='f1',
-                 output_names=None, label_names=None, average="macro"):
+                 output_names=None, label_names=None, threshold=0.5, average="macro"):
+        self.average = average
+        self.metrics = _BinaryClassificationMetrics(threshold=threshold)
+        EvalMetric.__init__(self, name=name,
+                            output_names=output_names, label_names=label_names,
+                            has_global_stats=True)
+
+    def update(self, labels, preds):
+        """Updates the internal evaluation result.
+
+        Parameters
+        ----------
+        labels : list of `NDArray`
+            The labels of the data.
+
+        preds : list of `NDArray`
+            Predicted values.
+        """
+        labels, preds = check_label_shapes(labels, preds, True)
+
+        for label, pred in zip(labels, preds):
+            self.metrics.update_binary_stats(label, pred)
+
+        if self.average == "macro":
 
 Review comment:
   In fact, `macro averaging` + F1 does not mean to average the F1 of each batch. I think we should revise it to be the same as https://scikit-learn.org/stable/modules/generated/sklearn.metrics.f1_score.html .

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