What effect does the dropout technique have on the learning process in neural networks?

It randomly disables a subset of neurons during training to avoid over$-$reliance on any single feature.

It decreases the variability in model predictions.

It speeds up the training by simplifying the network.

It uniformly reduces neuron numbers across all layers.