Anastassia Loukina comments

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                                            Anastassia Loukina

Investigate whether we can use any visualizers from Yellowbrick

Nice!

Kappa computation when predicted scores are on a different scale

Yes, this happens for raw scores. I suppose it is possible that the new predictions would be wildly out of scale but yet overlap with the human labels and we...

Kappa computation when predicted scores are on a different scale

For kappa computation the set of possible kappa labels is defined as all integers between `min(min(human), min(system)` and `max(max(human), max(system))`. This is what I mean by `range`. In the example...

Kappa computation when predicted scores are on a different scale

The goal is to make sure that the users get kappa value assuming we can compute it. We can go for 500,000,000 based on https://stackoverflow.com/questions/855191/how-big-can-a-python-list-get or set it to 100,000...

Kappa computation when predicted scores are on a different scale

So if the range is 6, we allow for example 60?

Kappa computation when predicted scores are on a different scale

No, I don't think so. I suppose theoretically you could end up with human 1,2,3,4 and system 1, 200, 400, 600 but kappas won't be particularly meaningful in this case....

Don't update user's jupyter history when notebooks are executed

@mulhod Is this something you are still planning to address/see as an issue?

Output file or directory in rsmpredict

I see the point about consistency, although I can see myself being very annoyed as a user: if I am running multiple experiments, I will end up with lots of...

Replace all path operations and functions with `pathlib`

Also related to #385

Consistent approach to warnings

We have a few inconsistencies in how we apply this. For example we raise UserWarning when computing partial correlations. Another concern I have is that on user side both types...