What is the full name of the ELU activation function?

The full name of the ELU activation function is Exponential Linear Unit. This activation function is widely used in neural networks due to its ability to alleviate the vanishing gradient problem and its smooth, differentiable nature. The ELU combines benefits from both linear and non-linear activation functions, allowing for faster learning and better performance in deep learning models compared to traditional activations like ReLU.

The "Exponential" part refers to the way the negative inputs are transformed, which follows an exponential curve, providing a non-zero output for negative values and helping to maintain the mean of the activations nearer to zero. This capability of producing negative outputs, unlike some other activation functions, contributes to effective training dynamics in deeper networks. This characteristic is key in enabling the model to learn more complex patterns.

Other options do not represent established names for the ELU function within the context of machine learning, which is why they are not correct.