Dropout
A regularization technique that randomly disables neurons during training to prevent co-adaptation and reduce overfitting.
In more detail
Dropout randomly sets neuron activations to zero during training with probability p. This forces networks to learn redundant representations. Disabled during inference. Highly effective for regularization and improving generalization.
Examples
- Dropout rate 0.5 in hidden layers
- Spatial dropout for CNNs
- Recurrent dropout for RNNs
Related terms
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