Are You a Dropout Regularization Pro?

Adding labeled data to the training set

Training on adversarial examples

A technique where randomly selected neurons are ignored during training (correct)

Adding noise to the input data

To add noise to the input data

To reduce the number of neurons in the network

To learn multiple independent internal representations (correct)

To improve the accuracy of the model

Increasing the number of layers in the network

Adding noise, adding unlabeled data, adding other tasks (correct)

Dropping out all neurons except for a few

Training on adversarial examples

<p>A technique where randomly selected neurons are ignored during training.</p> Signup and view all the answers

<p>To result in multiple independent internal representations being learned by the network</p> Signup and view all the answers

<p>Adding noise</p> Signup and view all the answers