A SAS DLPy image classification model achieves high training accuracy but poor validation accuracy. A practitioner adds Dropout layers after the dense layers. What role do Dropout layers play during training?

B is correct because Dropout randomly sets a fraction (drop rate) of neuron outputs to zero during each training step. This prevents neurons from co-adapting, forces the network to distribute knowledge across multiple pathways, and acts as an ensemble of many subnetworks — reducing overfitting. A is wrong; learning rate scheduling is separate. C describes Batch Normalization. D is wrong; Dropout is random and temporary during training, not permanent pruning.