This packages provides a template for adding new learners for mlr3.
Creating new learners is covered in detail in section "Adding new learners" in the mlr3book. This package serves as a starting point for learners to share with others.
This repository is a template repository to create a learner that aligns with existing mlr3 learners. Perform the following tasks to create your learner:
<package>
with the name of the underlying package.<type>
with the learner type, e.g. Classif
or Regr
.<algorithm>
with the name of the algorithm, e.g randomForest
.importance()
method in the respective learner class.oob_error()
method in the respective learner class.DESCRIPTION
..github/workflows
.<package>
in l.17 of tic.R
with the name of the package.inst/paramtest/
to ensure no parameter was forgotten in the learner.
Make sure that the CI test passes for "Param Check".README.md
with the package name.devtools::document(roclets = c('rd', 'collate', 'namespace'))
to create the NAMESPACE and man/ files.man-roxygen
as they are - they will just work.usethis::use_tidy_description()
to format DESCRIPTION
.devtools::test()
rcmdcheck::rcmdcheck()
Last but not least go through
:point_right: this checklist :page_facing_up:
to make sure your learner is ready for review.
After your learner is accepted, it can be added to mlr3learners.drat, making it installabe via the canonical install.packages()
function without the need to live on CRAN.
Resources for adding a new learner (summary)
!Important!: Delete all instructions up to this point and just leave the part below.
Adds <algorithm1>
and <algorithm2>
from the {} package to {mlr3}.
Install the latest release of the package via
install.packages("mlr3learners.<package>")
by following the instructions in the mlr3learners.drat README.
Alternatively, you can install the latest version of {mlr3learners.} from Github with:
remotes::install_github("mlr3learners/mlr3learners.<package>")
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.