Choose all correct statements about Domain Adversarial Neural Network $($DANN$).$

$1.$ It requires labeled data from both the source and target domains.

$2.$ No answer.

$3.$ It aims to reduce the difference in feature distribution between the source and target domains so that models trained on the source domain perform well on the target domain.

$4.$ It maximizes the performance of the domain discriminator to clearly separate the source and target domains.

$5.$ It is a neural network consisting of a classifier, a feature extractor, and a domain discriminator.