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

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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.

Por esta razón, los clasificadores binarios suelen utilizar una única neurona de salida con activación sigmoide en lugar de dos neuronas con softmax — son matemáticamente equivalentes.

Revision as of 03:17, 27 April 2026 (view source) DeployBot (talk \| contribs) (Batch translate Softmax Function unit 23 → es) Tag: translation		Revision as of 22:04, 27 April 2026 (view source) DeployBot (talk \| contribs) (Batch translate Softmax Function unit 23 → es) Tag: translation Newer edit →
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	Por ~~eso~~ los clasificadores binarios suelen utilizar una única neurona de salida con activación sigmoide en lugar de dos neuronas con softmax — son matemáticamente equivalentes.		Por esta razón, los clasificadores binarios suelen utilizar una única neurona de salida con activación sigmoide en lugar de dos neuronas con softmax — son matemáticamente equivalentes.