Closed henrifnk closed 3 years ago
mlr3learners.nnet is ready for review now.
[x] Watch out for the correct repo description: "Learner from {nnet} package for mlr3 "
[x] This reads weak: https://github.com/henrifnk/mlr3learners.nnet/blob/e71366f73cbb8a268f889e9678d501d013981542/R/LearnerClassifnnet.R#L13. If it has no default, it can not have an entry in "actual default". Please check again.
[x] Try to format the paramtest test files a bit more (l.15++)
[x] The predict functions must also be tested in the ParamTest
[x] The multinom learner already lives in {mlr3learners}
The predict functions must also be tested in the ParamTest
can you send me a link to an example where this is used?
all learners in {mlr3learners}
mlr3learners.nnet is ready for another review now.
You can find
mlr3learners.nnet
here. I'll move the learner tomlr3learners
and do drat once your review is doneChecklist before requesting a review
[x] Run
styler::style_pkg(style = styler::mlr_style)
(installpat-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 theDESCRIPTION
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.