mlr3learners

Package website: release | dev

This packages provides essential learners for mlr3, maintained by the mlr-org team. Additional learners can be found in the mlr3extralearners package on GitHub. Request additional learners over there.

👉 Table of all learners

Installation

# CRAN version:
install.packages("mlr3learners")

# Development version:
remotes::install_github("mlr-org/mlr3learners")

If you also want to install all packages of the connected learners, set dependencies = TRUE:

# CRAN version:
install.packages("mlr3learners", dependencies = TRUE)

# Development version:
remotes::install_github("mlr-org/mlr3learners", dependencies = TRUE)

Classification Learners

ID	Learner	Package
classif.cv_glmnet	Penalized Logistic Regression	glmnet
classif.glmnet	Penalized Logistic Regression	glmnet
classif.kknn	k-Nearest Neighbors	kknn
classif.lda	LDA	MASS
classif.log_reg	Logistic Regression	stats
classif.multinom	Multinomial log-linear model	nnet
classif.naive_bayes	Naive Bayes	e1071
classif.nnet	Single Layer Neural Network	nnet
classif.qda	QDA	MASS
classif.ranger	Random Forest	ranger
classif.svm	SVM	e1071
classif.xgboost	Gradient Boosting	xgboost

Regression Learners

ID	Learner	Package
regr.cv_glmnet	Penalized Linear Regression	glmnet
regr.glmnet	Penalized Linear Regression	glmnet
regr.kknn	k-Nearest Neighbors	kknn
regr.km	Kriging	DiceKriging
regr.lm	Linear Regression	stats
regr.ranger	Random Forest	ranger
regr.svm	SVM	e1071
regr.xgboost	Gradient Boosting	xgboost

Survival Learners (via mlr3proba)

ID	Learner	Package
surv.cv_glmnet	Penalized Cox Regression	glmnet
surv.glmnet	Penalized Cox Regression	glmnet
surv.ranger	Random Forest	ranger
surv.xgboost	Gradient Boosting	xgboost