Suggestion: Write classes for classification and statistics

hi,
i am currently doing my first analysis in MNE. i got aware that at a lot of steps in the workflow, data is conveniently represented in classes (raw, epochs, average, TFR, etc....). this seems to be lacking for classification and statistics.

as i am going to wrap these two things in classes anyhow to make my life easier, i thought it would be a good idea to ask for your input first because if it is deemed useful by you, i would be happy to contribute the code to MNE.

my current idea is basically to make statistics results a subclass of Average (for evoked data, haven't thought about tfr data yet...). it would need some additional fields but it could basically reuse a lot of functionality, because it is quite similar.

classification seems a bit less straight forward because the "main" result is the scores and one would need to take care of folds, weights and projections.

so, i am curious what you think!

No file, test, entry point, or concrete acceptance criteria is named. Start by reviewing the existing Raw, Epochs, Average, and TFR class APIs alongside the discussion, then establish whether statistics and classification need separate result models; done requires an agreed scope and design before implementation.