Develop #10
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Develop #10
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pat-alt
commented
Oct 15, 2022
pat-alt
commented
- Wrapping models not machines.
- Distinction between inductive and transductive.
- Added Jackknife.
…result, Xnew) on wrapped EvoTrees models fails for some reason.
…ctions for classifiers, I need access to data -> labels(y). Not sure how to do this when treating ConformalModels just as Model, since only machines have access to data.
5 wrap models not machines
This was referenced Oct 15, 2022
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ablaom
reviewed
Oct 17, 2022
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| # Conformal prediction through dispatch: | ||
| """ | ||
| MMI.predict(conf_model::ConformalModel, Xnew, coverage::AbstractFloat=0.95) |
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Type piracy? MMI.predict(::Model, ...) will always have a fitresult as the second argument here. And your method has an extra parameter coverage, which doesn't really fit into the MLJ API at all, unless you make it a hyperparameter (field of the model).
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Yep. We have already have Interval <: Supervised but maybe can extend that further. Related is helping me out with this list of "target proxies" (predictions types) for the future.
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