I am looking to train a neural network to solve a supervised classification task. But one of my input features is a categorical variable that can have more than a few billion possible values.
For example, one crucial input for my problem is the IP address, and I have >4B values in my dataset. I don’t think having a one-hot vector of that size would be feasible.
Is there any way to deal with this type of inputs?