dropout works as regularization: it approximates an ensemble of subnetworks

Why does turning off neurons randomly help a brainy computer learn better?

Imagine you're teaching a friend to recognize different types of fruit. You show them many pictures but don't tell them all the details. Over time, they start guessing correctly more often.

Dropout training is like showing your friend random fruit pictures without labels. It forces the computer's brain to learn from different guesses, making it better at guessing on its own.

Example

If you show your friend 10 pictures of apples and 10 pictures of oranges without telling them which is which, they'll start guessing correctly more often after seeing many pictures.

Remember this

Dropout training helps computers learn better by making them guess on their own, just like your friend guessing fruit types.

Text adapted from Wikipedia, licensed under CC BY-SA 4.0.

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