Package: mlr3learners 0.7.0

Marc Becker

mlr3learners: Recommended Learners for 'mlr3'

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.

Authors:Michel Lang [aut], Quay Au [aut], Stefan Coors [aut], Patrick Schratz [aut], Marc Becker [cre, aut]

mlr3learners_0.7.0.tar.gz
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mlr3learners_0.7.0.tgz(r-4.4-any)mlr3learners_0.7.0.tgz(r-4.3-any)
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mlr3learners.pdf |mlr3learners.html✨
mlr3learners/json (API)
NEWS

# Install 'mlr3learners' in R:
install.packages('mlr3learners', repos = c('https://mlr-org.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/mlr-org/mlr3learners/issues

On CRAN:

classificationlearnersmachine-learningmlr3regression

21 exports 89 stars 4.90 score 21 dependencies 10 dependents 1 mentions 1.4k scripts 4.4k downloads

Last updated 2 months agofrom:26ee915f86 (on v0.7.0). Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 29 2024
R-4.5-winOKAug 29 2024
R-4.5-linuxOKAug 29 2024
R-4.4-winOKAug 29 2024
R-4.4-macOKAug 29 2024
R-4.3-winOKAug 29 2024
R-4.3-macOKAug 29 2024

Exports:LearnerClassifCVGlmnetLearnerClassifGlmnetLearnerClassifKKNNLearnerClassifLDALearnerClassifLogRegLearnerClassifMultinomLearnerClassifNaiveBayesLearnerClassifNnetLearnerClassifQDALearnerClassifRangerLearnerClassifSVMLearnerClassifXgboostLearnerRegrCVGlmnetLearnerRegrGlmnetLearnerRegrKKNNLearnerRegrKMLearnerRegrLMLearnerRegrNnetLearnerRegrRangerLearnerRegrSVMLearnerRegrXgboost

Dependencies:backportscheckmatecodetoolsdata.tabledigestevaluatefuturefuture.applyglobalslgrlistenvmlbenchmlr3mlr3measuresmlr3miscpalmerpenguinsparadoxparallellyPRROCR6uuid

Readme and manuals

Help Manual

Help pageTopics
mlr3learners: Recommended Learners for 'mlr3'mlr3learners-package mlr3learners
GLM with Elastic Net Regularization Classification LearnerLearnerClassifCVGlmnet mlr_learners_classif.cv_glmnet
GLM with Elastic Net Regularization Classification LearnerLearnerClassifGlmnet mlr_learners_classif.glmnet
k-Nearest-Neighbor Classification LearnerLearnerClassifKKNN mlr_learners_classif.kknn
Linear Discriminant Analysis Classification LearnerLearnerClassifLDA mlr_learners_classif.lda
Logistic Regression Classification LearnerLearnerClassifLogReg mlr_learners_classif.log_reg
Multinomial log-linear learner via neural networksLearnerClassifMultinom mlr_learners_classif.multinom
Naive Bayes Classification LearnerLearnerClassifNaiveBayes mlr_learners_classif.naive_bayes
Classification Neural Network LearnerLearnerClassifNnet mlr_learners_classif.nnet
Quadratic Discriminant Analysis Classification LearnerLearnerClassifQDA mlr_learners_classif.qda
Ranger Classification LearnerLearnerClassifRanger mlr_learners_classif.ranger
Support Vector MachineLearnerClassifSVM mlr_learners_classif.svm
Extreme Gradient Boosting Classification LearnerLearnerClassifXgboost mlr_learners_classif.xgboost
GLM with Elastic Net Regularization Regression LearnerLearnerRegrCVGlmnet mlr_learners_regr.cv_glmnet
GLM with Elastic Net Regularization Regression LearnerLearnerRegrGlmnet mlr_learners_regr.glmnet
k-Nearest-Neighbor Regression LearnerLearnerRegrKKNN mlr_learners_regr.kknn
Kriging Regression LearnerLearnerRegrKM mlr_learners_regr.km
Linear Model Regression LearnerLearnerRegrLM mlr_learners_regr.lm
Neural Network Regression LearnerLearnerRegrNnet mlr_learners_regr.nnet
Ranger Regression LearnerLearnerRegrRanger mlr_learners_regr.ranger
Support Vector MachineLearnerRegrSVM mlr_learners_regr.svm
Extreme Gradient Boosting Regression LearnerLearnerRegrXgboost mlr_learners_regr.xgboost