Translations:Overfitting and Regularization/22/es: Difference between revisions

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Message definition (Overfitting and Regularization)

'''{{Term|dropout}}''' (Srivastava et al., 2014) is a regularization technique specific to neural networks. During training, each neuron is randomly "dropped" (set to zero) with probability <math>p</math> at each forward pass. This prevents neurons from co-adapting and forces the network to learn redundant representations.

dropout (Srivastava et al., 2014) es una técnica de regularización específica para redes neuronales. Durante el entrenamiento, cada neurona se "descarta" aleatoriamente (se pone a cero) con probabilidad $$ p $$ en cada paso hacia adelante. Esto impide que las neuronas se coadapten y obliga a la red a aprender representaciones redundantes.

Revision as of 03:39, 27 April 2026 (view source) DeployBot (talk \| contribs) (Batch translate Overfitting and Regularization unit 22 → es) Tag: translation		Latest revision as of 23:40, 27 April 2026 (view source) DeployBot (talk \| contribs) (Batch translate Overfitting and Regularization unit 22 → es) Tag: translation
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	'''~~Dropout~~''' (Srivastava et al., 2014) es una técnica de regularización específica para redes neuronales. Durante el entrenamiento, cada neurona se "descarta" aleatoriamente (se ~~establece en~~ cero) con probabilidad <math>p</math> en cada paso hacia adelante. Esto ~~evita~~ que las neuronas se coadapten y obliga a la red a aprender representaciones redundantes.		'''{{Term\|dropout}}''' (Srivastava et al., 2014) es una técnica de regularización específica para redes neuronales. Durante el entrenamiento, cada neurona se "descarta" aleatoriamente (se pone a cero) con probabilidad <math>p</math> en cada paso hacia adelante. Esto impide que las neuronas se coadapten y obliga a la red a aprender representaciones redundantes.