training
Dropout
A regularization technique where random neurons are temporarily disabled during training, forcing the network to learn redundant representations. This prevents the network from becoming overly dependent on any single neuron and improves generalization.
In practice
With 50% dropout, half of the neurons in a layer are randomly turned off during each training step.