ELU (Exponential Linear Unit)

The Exponential Linear Unit (ELU) is a type of activation function used in artificial neural networks. It transforms the input data to help the network learn better. Unlike simpler functions like ReLU, which can cause issues when inputs are negative, ELU allows for negative outputs. This helps maintain mean activation closer to zero, improving learning efficiency. Essentially, ELU combines the benefits of linear behavior for positive values with an exponential approach for negative values, enhancing the model's ability to capture complex patterns in data. This functionality can lead to more accurate predictions in tasks like image and speech recognition.