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What Is A Dropout?

Answer»

DROPOUT is a regularization technique for reducing overfitting in NEURAL networks. At each training step we randomly drop out (SET to zero) set of nodes, thus we create a different model for each training case, all of these models share WEIGHTS. It’s a FORM of model averaging.

Dropout is a regularization technique for reducing overfitting in neural networks. At each training step we randomly drop out (set to zero) set of nodes, thus we create a different model for each training case, all of these models share weights. It’s a form of model averaging.



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