Anthony Blaom, PhD
Anthony Blaom, PhD
@ashryaagr Are you able to address this soon?
That's fine. Perhaps you want to consider adding me or Sebastian as a Collaborator with admin access to bump the [bus factor](https://en.wikipedia.org/wiki/Bus_factor) of this package?
Still broken.
@salbalkus Yes, currently `evaluate!` is limited to models that can `predict`, which does include outlier detection models, but not general unsupervised models. I think your suggestion to add some kind...
In the meantime, you might be able to implement what you want using a learning network as well. The MLJ `Stack` composite model is implemented using learning networks, and there...
@CameronBieganek @tylerjthomas9
This is great feedback, thanks. I'm torn between dumping mutation altogether (advantage: simplicity) and proceeding as I propose above (convenience). Some context: In a summer project we are working on...
Okay, I now remember the reason for the existing behaviour. The use case is evaluating models that support "warm restart". If using `Holdout()` (or other single test/train pair of row...
Good catch, thanks. Yes the intention is that calling `clean!(model)` immediately after `clean!(model)` should not mutate `model`. So, ```julia clean!(model) clone = deepcopy(model) clean!(model) @assert model == clone ``` ```