Connect learner logspline from package logspline

[RaphaelS1]

Checklist before requesting a review

• [x] Run styler::style_pkg(style = styler::mlr_style) (install pat-s/styler@mlr-style if not yet done)

• [x] Run lintr::lint_package() and fix all issues.

• [x] Run usethis::use_tidy_description() to format the DESCRIPTION file.

• [x] Check that the learner package name is all lower case, e.g. mlr3learners.partykit.

• [x] Ensure that there are not leftover of <package>, <algorithm> or <type> within the learner repo.

• [x] Ensure that the "Parameter Check" passed in the CI (both for the train and predict functions)

• [x] Ensure that "R CMD check" passed in the CI.

• [x] Check that your learners upstream package is not listed in the "Imports" but in the "Suggests" section within the DESCRIPTION file.

• [x] If you changed any parameter defaults: Did you document the change (reason and new default) in the help page of the respective learner?

• [x] Open a Pull Request in the mlr3learners repo to add your learner to the list of "In Progress" learners. Once approved, it will be moved to the "Approved" section.

[RaphaelS1]

Ready for review!

https://github.com/mlr3learners/mlr3learners.logspline

[pat-s]

Thanks. As per your comment in the {np} learner you would have to add #nolint to all of the empty functions: https://github.com/mlr3learners/mlr3learners.logspline/blob/e02dd32aca0783b539717a96d775deb39abdede4/R/LearnerDensLogspline.R#L68-L69

This applies to a few more learners that are open for review.

Otherwise 👍

[RaphaelS1]

deployed - will check the others now