make lightgbm raw classification predictions backward and forward compatible

[jameslamb]

Contributes to #34.

As of microsoft/LightGBM#5133, lightgbm:::predict.lgb.Booster() no longer supports keyword arguments rawscore, predcontrib, or predleaf.

Those were replaced by equivalent values to the type argument, for consistency with how most statistical models in R work (from both the standard library and 3rd-party packages).

bst <- lgb.train(...)

# before
predict(bst, X, rawscore = TRUE)

# after
predict(bst, X, type = "raw")

Because of the current state of development in LightGBM, we made the difficult choice to make this change in a non-backwards-compatible way, without a deprecation cycle (microsoft/LightGBM#5133 (review)).

{bonsai} provides support for generating raw-score predictions from {lightgbm} models, but that functionality isn't currently covered by tests.

Checked with {covr}.

Rscript \
    --vanilla \
    -e "covr::report(covr::package_coverage(), file = file.path(getwd(), 'coverage.html'))"

This PR proposes adding a small patch to make {bonsai} compatible with previous and future releases of {lightgbm}, so that the eventual release of {lightgbm} v4.0.0 will hopefully not be disruptive.

It also adds unit tests generating raw predictions for classification models, to cover this functionality and increase the chance of catching future incompatibilities.

How I tested this

Tested against the development version of {lightgbm} following using the approach described in #34 (comment).

Notes for Reviewers

The unit tests I've added are just enough to cover the relevant code and minimally test that it's producing expected results. If you'd prefer stricter tests, please let me know and I'd be happy to add them.

Thanks very much for your time and consideration.

[simonpcouch]

This looks super clean, thanks @jameslamb! The context is much appreciated, too.

Will go ahead and merge.🚀

[jameslamb]

Thanks very much!

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