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ReLu is not the only option. However, due to way it functions it is one of the fastest activation function. Its good to experiment with other activation functions too, though there is no guarantee of improved model performance on account of activation function alone.
To my knowledge, using Leaky ReLu will help reduce impact of vanishing gradient and also reduce impact of dead neurons as in case of ReLu, wherein the negative values become 0.
Can you use any of the ReLU activation functions in SPSS 29? All I see is Sigmoid and Htang. Can I code in the other functions? I appreciate your consideration.