mlr3learners

mlr3learners-package

<p>More learners are available in the <code>mlr3learners</code> repository on Github (<a href="https://github.com/mlr3learners">https://github.com/mlr3learners</a>).
There also is a wiki page listing all currently available custom learners (<a href="https://github.com/mlr-org/mlr3learners/wiki/Extra-Learners">https://github.com/mlr-org/mlr3learners/wiki/Extra-Learners</a>).
A guide on how to create custom learners is covered in the book: <a href="https://mlr3book.mlr-org.com">https://mlr3book.mlr-org.com</a>.
Feel invited to contribute a missing learner to the mlr3 ecosystem!</p>

Recommended Learners for 'mlr3'. Extends 'mlr3'
with interfaces to essential machine learning packages on CRAN.  This
includes, but is not limited to: (penalized) linear and logistic
regression, linear and quadratic discriminant analysis, k-nearest
neighbors, naive Bayes, support vector machines, and gradient
boosting.

Michel Lang

Recommended Learners for 'mlr3'

Quay Au

Stefan Coors

Patrick Schratz

mlr3learners-package function

<p>More learners are available in the <code>mlr3learners</code> repository on Github (<a href='https://github.com/mlr3learners'>https://github.com/mlr3learners</a>).
There also is a wiki page listing all currently available custom learners (<a href='https://github.com/mlr-org/mlr3learners/wiki/Extra-Learners'>https://github.com/mlr-org/mlr3learners/wiki/Extra-Learners</a>).
A guide on how to create custom learners is covered in the book: <a href='https://mlr3book.mlr-org.com'>https://mlr3book.mlr-org.com</a>.
Feel invited to contribute a missing learner to the mlr3 ecosystem!</p>

mlr3learners-package: mlr3learners: Recommended Learners for 'mlr3'

Description

Arguments

See Also