mboost: Model-Based Boosting
Functional gradient descent algorithm (boosting) for optimizing general risk functions utilizing component-wise (penalised) least squares estimates or regression trees as base-learners for fitting generalized linear, additive and interaction models to potentially high-dimensional data. Models and algorithms are described in <doi:10.1214/07-STS242>, a hands-on tutorial is available from <doi:10.1007/s00180-012-0382-5>. The package allows user-specified loss functions and base-learners.
| Version: | 2.9-11 |
| Depends: | R (≥ 3.2.0), methods, stats, parallel,stabs (≥ 0.5-0) |
| Imports: | Matrix,survival (≥ 3.2-10), splines,lattice,nnls,quadprog, utils, graphics, grDevices,partykit (≥ 1.2-1) |
| Suggests: | TH.data,MASS,fields,BayesX,gbm,mlbench,RColorBrewer,rpart (≥ 4.0-3),randomForest,nnet,testthat (≥ 0.10.0),kangar00 |
| Published: | 2024-08-22 |
| DOI: | 10.32614/CRAN.package.mboost |
| Author: | Torsten Hothorn [cre, aut], Peter Buehlmann [aut], Thomas Kneib [aut], Matthias Schmid [aut], Benjamin Hofner [aut], Fabian Otto-Sobotka [ctb], Fabian Scheipl [ctb], Andreas Mayr [ctb] |
| Maintainer: | Torsten Hothorn <Torsten.Hothorn at R-project.org> |
| BugReports: | https://github.com/boost-R/mboost/issues |
| License: | GPL-2 |
| URL: | https://github.com/boost-R/mboost |
| NeedsCompilation: | yes |
| Citation: | mboost citation info |
| Materials: | NEWS |
| In views: | MachineLearning,Survival |
| CRAN checks: | mboost results |
Documentation:
| Reference manual: | mboost.html ,mboost.pdf |
| Vignettes: | Survival Ensembles (source,R code) mboost (source,R code) mboost Illustrations (source,R code) mboost Tutorial (source,R code) |
Downloads:
| Package source: | mboost_2.9-11.tar.gz |
| Windows binaries: | r-devel:mboost_2.9-11.zip, r-release:mboost_2.9-11.zip, r-oldrel:mboost_2.9-11.zip |
| macOS binaries: | r-release (arm64):mboost_2.9-11.tgz, r-oldrel (arm64):mboost_2.9-11.tgz, r-release (x86_64):mboost_2.9-11.tgz, r-oldrel (x86_64):mboost_2.9-11.tgz |
| Old sources: | mboost archive |
Reverse dependencies:
| Reverse depends: | boostrq,FDboost,gamboostLSS,gfboost,InvariantCausalPrediction,mermboost,tbm |
| Reverse imports: | biospear,bujar,carSurv,censored,DIFboost,EnMCB,GeDS,geoGAM,mgwrsar,RobustPrediction,sgboost,survML,visaOTR |
| Reverse suggests: | catdata,CompareCausalNetworks,familiar,HSAUR2,HSAUR3,imputeR,MachineShop,MLInterfaces,mlr,mlr3fda,pathMED,pre,spikeSlabGAM,sqlscore,stabs,survex,tidyfit |
Linking:
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