I am beginning to learn how to use
scikit-learn and I have a hard time choosing the right model.
Here is my dataset: I have 100 persons. Each person was measured three times: baseline, first event and second event. Each measurement had 100 different markers per person that range from 0.1 to 1000. Additionally I have outcome measurements of each event: outcome can be 0, 1 or 2. My task is to find just a few markers (let’s say 10) that can predict outcome with a good accuracy. If I am right it should be: Supervised learning/Classification problem. What model would be the best?
Thanks for your help!