Dropout increases the model’s training error but decreases the test error, preventing overfitting.Group of answer choicesTrueFalse

The use of dropout in a neural network can help reduce the risk of overfitting.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

Overfitting occurs when a model performs well on training data but poorly on unseen data.Group of answer choicesTrueFalse

Dropout prevents a neural network ____________.1 pointfrom overfittingfrom underfittingfrom ideal fit

With the inverted dropout technique, at test time: