I wish someone built something like this for generic classification. You give the system a bunch of folders. Each folder is a label containing corresponding samples. The system then creates a replica of the folder structure with no content. Each time you give it a new piece of data it places it in one of those newly created folders.

This is an interface truly anyone could use. Just call it "intelligent folders" or something. The user doesn't even need to know which algorithm it uses. Just split sample into training and test data at random and choose the algo that give best results.

I was working on this for text data, but then switched jobs and don't have energy to make this in my spare time right now.