Dropout (neural networks)
From Infogalactic: the planetary knowledge core
Dropout is a technique of reducing overfitting in neural networks by preventing complex co-adaptations on training data. It is a very efficient way of performing model averaging with neural networks.[1] The term "dropout" refers to dropping out units (both hidden and visible) in a neural network.[2]
