评测函数有问题

[MichelleYang2017]

keras里面的评测的ACC本质上计算是这样的：label：[[0,1,0,0],[0,0,0,1]]，pred:[[0,0,0,0],[0,0,0,1]]准确率不是50%,而是87.5%

[JasonZhang156]

keras使用‘accuracy’作为metrics时，默认调用的是metrics.py里的categorical_accuracy函数，如下 def categorical_accuracy(y_true, y_pred): '''Calculates the mean accuracy rate across all predictions for multiclass classification problems. ''' return K.mean(K.equal(K.argmax(y_true, axis=-1), K.argmax(y_pred, axis=-1)))

我认为计算方法是没有问题。

[MichelleYang2017]

eras使用‘accuracy’作为metrics时，默认调用的是metrics.py里的accuracy(y_true, y_pred)函数吧，当指定为metrics.categorical_accuracy才用的是categorical_accuracy函数吧

[JasonZhang156]

默认调用categorical_accuracy，可以参考training.py

[MichelleYang2017]

ok，感谢

z小白 [email protected] 于2019年12月5日周四 下午6:23写道：

默认调用categorical_accuracy，可以参考training.py https://github.com/fchollet/keras/blob/d8b226f26b35348d934edb1213061993e7e5a1fa/keras/engine/training.py#L651

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