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

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

    Revision as of 22:02, 27 April 2026

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    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.

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

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