Translations:Softmax Function/23/zh: Difference between revisions

Latest revision as of 23:41, 27 April 2026

Information about message (contribute)

This message has no documentation. If you know where or how this message is used, you can help other translators by adding documentation to this message.

Message definition (Softmax Function)

This is why binary classifiers typically use a single output neuron with a sigmoid {{Term|activation function|activation}} rather than two neurons with softmax — they are mathematically equivalent.

这就是为什么二分类器通常使用带有 sigmoid 激活函数的单个输出神经元，而不是使用 softmax 的两个神经元——它们在数学上是等价的。

Revision as of 22:04, 27 April 2026 (view source) DeployBot (talk \| contribs) (Batch translate Softmax Function unit 23 → zh) Tag: translation ← Older edit		Latest revision as of 23:41, 27 April 2026 (view source) DeployBot (talk \| contribs) (Batch translate Softmax Function unit 23 → zh) Tag: translation
Line 1:		Line 1:
	~~这就是为什么二元分类器通常使用带~~ sigmoid ~~激活的单个输出神经元，而不是带~~ softmax ~~的两个神经元——二者在数学上是等价的。~~		这就是为什么二分类器通常使用带有 sigmoid {{Term\|activation function\|激活函数}}的单个输出神经元，而不是使用 softmax 的两个神经元——它们在数学上是等价的。