I am doing a project that involves training and testing different algorithms to predict a developer's profile type (Frontend, Fullstack, QA, ML, etc.) using that developer's skills (AWS, Selenium, Hadoop, Java, etc.).
I am looking more in depth at correct and incorrect classifications made by the Logistic Regression (OVR) algorithm to understand whether the presence or absence of particular skills cause this to happen. With my example, I use Fullstack-Fullstack as a correct classification and Fullstack-ML as incorrect.
My question is: is one more important than the other? In other words, is it more important to look at the skills absent or present?
Thank you so much for the help!