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

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

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

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

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 techniques performs similar operations as a dropout in a neural network?Question 5Select one:A.StackingB.NoneC.BoostingD.Bagging