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.
| Version: | 2.8-1 |
| Depends: | R (≥ 2.14.0), methods, stats, parallel, stabs (≥ 0.5-0) |
| Imports: | Matrix, survival, splines, lattice, nnls, quadprog, utils, graphics, grDevices, party (≥ 1.1-0) |
| Suggests: | TH.data, MASS, fields, BayesX, gbm, mlbench, RColorBrewer, rpart (≥ 4.0-3), randomForest, nnet, testthat (≥ 0.10.0), kangar00 |
| Published: | 2017-07-23 |
| Author: | Torsten Hothorn [aut], Peter Buehlmann [aut], Thomas Kneib [aut], Matthias Schmid [aut], Benjamin Hofner [aut, cre], Fabian Sobotka [ctb], Fabian Scheipl [ctb], Andreas Mayr [ctb] |
| Maintainer: | Benjamin Hofner <benjamin.hofner at pei.de> |
| 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: | README NEWS |
| In views: | MachineLearning, Survival |
| CRAN checks: | mboost results |
| Reference manual: | mboost.pdf |
| Vignettes: |
Survival Ensembles mboost mboost Illustrations mboost Tutorial |
| Package source: | mboost_2.8-1.tar.gz |
| Windows binaries: | r-devel: mboost_2.8-1.zip, r-release: mboost_2.8-1.zip, r-oldrel: mboost_2.8-1.zip |
| OS X El Capitan binaries: | r-release: mboost_2.8-1.tgz |
| OS X Mavericks binaries: | r-oldrel: mboost_2.8-1.tgz |
| Old sources: | mboost archive |
| Reverse depends: | CAM, FDboost, gamboostLSS, globalboosttest, InvariantCausalPrediction, parboost |
| Reverse imports: | biospear, bujar, DIFboost, gamboostMSM, geoGAM, imputeR, SurvRank |
| Reverse suggests: | catdata, Daim, fscaret, HSAUR2, HSAUR3, mlr, spikeSlabGAM, sqlscore, stabs |
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