How to find the input variables for a classification problem?
Two approaches come to mind:


Use all of them and perform feature selection to identify indicative features. Algorithms include Information Gain and Mutual Information.
Hand-pick some features you deem indicative intuitively, or delete the ones you deem non-indicative.


Generally, you have some sort of hypothesis that you are testing where you attest the capability of (a subset of) your features (and the algorithm you'll use) to uniquely identify the label/class they belong to. The features you use are one of the most important things in the classification task. So it is good to spend time to intelligently find out which features contribute. 

For this task, you do have a lot of possible features so the automatic feature selection approach might be better.