My professor asked my class to make a neural network to try to predict if breast cancer is benign or malignant. To do this I'm using the Breast Cancer Wisconsin (Diagnostic) Data Set.
As a tip for doing this my professor said not all 30 attributes needs to be used as an input (there are 32, but the first 2 are the ID and Diagnosis), what I want to ask is: How am I supposed to take those 30 inputs (that would create like 100+ weights depending on how many neurons I would use) and get them into a lesser number?
I've already found how to "prune" a neural net, but I don't think that's what I want. I'm not trying to eliminate unnecessary neurons but to shrink the input itself.
PS: Sorry for any English errors, it's not my native language.