Dropout is a technique used to prevent overfitting by randomly turning off a fraction of neurons during training.Group of answer choicesTrueFalse

Dropout is a technique used to prevent overfitting by randomly turning off a fraction of neurons during training.Group of answer choicesTrueFalse

If a neural network with a single hidden layer uses dropout with a rate of 0.5, what fraction of neurons are turned off during each training step?

A common technique to reduce overfitting in neural networks is to apply ______________, which randomly drops units from the neural network during training.

Which of the following is NOT a type of regularization technique used in linear regression to prevent overfitting?

Which of the following techniques can help prevent overfitting in regression models?