Heres the task: I have data I don't know much about. The final task is to build a classifier to classify the samples into a few categories. Some of the categories are pretty clear, we can easily use these as labels for a classifier. But I guess there are more useful categories possible, because right now most of my samples don't belong to any category. As I am no expert in the specific field, I would like to use some clustering algorithm to show possible label ideas. When using traditional clustering algorithms, they find all sorts of patterns in the data I am not interested in.
So I am looking for a way to tell the algorithm: "Hey, find some clusters in my data, but please take the existing clusters (or labeled data) into account." This should tell the clustering algorithm what I am interested in, and in what not.
Does something like this exists? Or any other idea how to solve the problem of finding additional labels?
BTW: in my case, I am doing NLP.