Can a neural network learn too well?
Image: O'Connor P, Neil D, Liu S, Delbruck T, Pfeiffer M, CC BY 3.0, via Wikimedia Commons
Can a neural network learn too well?
Imagine you're memorizing a new language. You start to remember every word perfectly, but suddenly, you can't understand new sentences because you're relying too much on memorized phrases.
Dropout regularization is like taking breaks while memorizing a language to avoid relying too much on memorized phrases. This helps you understand new sentences better.
Example
If you practice 100 words a day, taking a break every 10 words helps you remember them better.
Remember this
Dropout helps neural networks generalize better by preventing them from relying too much on specific features.
Text adapted from Wikipedia, licensed under CC BY-SA 4.0.
dropout works as regularization: it approximates an ensemble of subnetworks
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