I don't think the wording of my question is that clear myself, but I don't have any better words suitable for a title (on top of my head at least). I was wondering if given features X that is classified by a model M as class C, is there a way to find the features Y that is relatively "close" to X so that it would be classified as class C' by M.
I was thinking if some sort of clustering can help such as k-means and then getting the centroid of class C' and using that. The final idea is to get the difference between X and Y to be displayed. Does that sound reasonable? I'm not really a data scientist so want to check up on my thoughts.
If someone can suggest a paper or direction that would be much appreciated
EDIT: For clarification. The purpose of this is that I have a set of people's skills and their jobs and I want to be able to give an advice of what skills a person needs to cultivate for their desired job.
E.g I can program, have a CS degree, experienced with unix etc. and am classified as software developer (skills are codified into numerical values not text anymore) and I want to work as a chemical engineer. I want to know the skills I would need so that I can be classified as fit to be a chemical engineer.
So X is my set of skills, C is software developer, C' is chemical engineer, and Y is the set of skills appropriate for a chemical engineer that I am looking for.