I am starting to study Neural Network. I want to build a MLP where I will feed it:
- 3 features which are continuous
- one feature which is categorical (48 classes)
How can I do this?
Before adding the categorical feature, I was using 'relu' activation function and 'lbfgs' as a solver in MLPRegrssor in sklearn.
I was wondering: how can I integrate this variable into the network? Should I do one-hot encoding? Should I keep relu as activation function or should I try sigmoid, softmax or something like that?