Package: mlr3learners 0.14.0
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:
mlr3learners_0.14.0.tar.gz
mlr3learners_0.14.0.zip(r-4.7)mlr3learners_0.14.0.zip(r-4.6)mlr3learners_0.14.0.zip(r-4.5)
mlr3learners_0.14.0.tgz(r-4.6-x86_64)mlr3learners_0.14.0.tgz(r-4.6-arm64)mlr3learners_0.14.0.tgz(r-4.5-x86_64)mlr3learners_0.14.0.tgz(r-4.5-arm64)
mlr3learners_0.14.0.tar.gz(r-4.7-arm64)mlr3learners_0.14.0.tar.gz(r-4.7-x86_64)mlr3learners_0.14.0.tar.gz(r-4.6-arm64)mlr3learners_0.14.0.tar.gz(r-4.6-x86_64)
mlr3learners_0.14.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
mlr3learners/json (API)
NEWS
| # Install 'mlr3learners' in R: |
| install.packages('mlr3learners', repos = c('https://mlr-org.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/mlr-org/mlr3learners/issues
Pkgdown/docs site:https://mlr3learners.mlr-org.com
classificationlearnersmachine-learningmlr3regression
Last updated from:68ac49a189 (on v0.14.0). Checks:11 ERROR, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | ERROR | 202 | ||
| linux-devel-x86_64 | ERROR | 203 | ||
| source / vignettes | OK | 244 | ||
| linux-release-arm64 | ERROR | 188 | ||
| linux-release-x86_64 | ERROR | 198 | ||
| macos-release-arm64 | ERROR | 151 | ||
| macos-release-x86_64 | ERROR | 284 | ||
| macos-oldrel-arm64 | ERROR | 177 | ||
| macos-oldrel-x86_64 | ERROR | 278 | ||
| windows-devel | ERROR | 177 | ||
| windows-release | ERROR | 175 | ||
| windows-oldrel | ERROR | 166 | ||
| wasm-release | OK | 125 |
Exports:LearnerClassifCVGlmnetLearnerClassifGlmnetLearnerClassifKKNNLearnerClassifLDALearnerClassifLogRegLearnerClassifMultinomLearnerClassifNaiveBayesLearnerClassifNnetLearnerClassifQDALearnerClassifRangerLearnerClassifSVMLearnerClassifXgboostLearnerRegrCVGlmnetLearnerRegrGlmnetLearnerRegrKKNNLearnerRegrKMLearnerRegrLMLearnerRegrNnetLearnerRegrRangerLearnerRegrSVMLearnerRegrXgboost
Dependencies:backportscheckmateclicodetoolsdata.tabledigestevaluatefuturefuture.applyglobalslgrlistenvmiraimlbenchmlr3mlr3measuresmlr3miscnanonextpalmerpenguinsparadoxparallellyPRROCR6rlanguuid
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| mlr3learners: Recommended Learners for 'mlr3' | mlr3learners-package mlr3learners |
| GLM with Elastic Net Regularization Classification Learner | LearnerClassifCVGlmnet mlr_learners_classif.cv_glmnet |
| GLM with Elastic Net Regularization Classification Learner | LearnerClassifGlmnet mlr_learners_classif.glmnet |
| k-Nearest-Neighbor Classification Learner | LearnerClassifKKNN mlr_learners_classif.kknn |
| Linear Discriminant Analysis Classification Learner | LearnerClassifLDA mlr_learners_classif.lda |
| Logistic Regression Classification Learner | LearnerClassifLogReg mlr_learners_classif.log_reg |
| Multinomial log-linear learner via neural networks | LearnerClassifMultinom mlr_learners_classif.multinom |
| Naive Bayes Classification Learner | LearnerClassifNaiveBayes mlr_learners_classif.naive_bayes |
| Classification Neural Network Learner | LearnerClassifNnet mlr_learners_classif.nnet |
| Quadratic Discriminant Analysis Classification Learner | LearnerClassifQDA mlr_learners_classif.qda |
| Ranger Classification Learner | LearnerClassifRanger mlr_learners_classif.ranger |
| Support Vector Machine | LearnerClassifSVM mlr_learners_classif.svm |
| Extreme Gradient Boosting Classification Learner | LearnerClassifXgboost mlr_learners_classif.xgboost |
| GLM with Elastic Net Regularization Regression Learner | LearnerRegrCVGlmnet mlr_learners_regr.cv_glmnet |
| GLM with Elastic Net Regularization Regression Learner | LearnerRegrGlmnet mlr_learners_regr.glmnet |
| k-Nearest-Neighbor Regression Learner | LearnerRegrKKNN mlr_learners_regr.kknn |
| Kriging Regression Learner | LearnerRegrKM mlr_learners_regr.km |
| Linear Model Regression Learner | LearnerRegrLM mlr_learners_regr.lm |
| Neural Network Regression Learner | LearnerRegrNnet mlr_learners_regr.nnet |
| Ranger Regression Learner | LearnerRegrRanger mlr_learners_regr.ranger |
| Support Vector Machine | LearnerRegrSVM mlr_learners_regr.svm |
| Extreme Gradient Boosting Regression Learner | LearnerRegrXgboost mlr_learners_regr.xgboost |
