mboost v2.9-4
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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.
Functions in mboost
| Name | Description | |
| FP | Fractional Polynomials | |
| boost_family-class | Class "boost\_family": Gradient Boosting Family | |
| confint.mboost | Pointwise Bootstrap Confidence Intervals | |
| cvrisk | Cross-Validation | |
| blackboost | Gradient Boosting with Regression Trees | |
| IPCweights | Inverse Probability of Censoring Weights | |
| Family | Gradient Boosting Families | |
| baselearners | Base-learners for Gradient Boosting | |
| mboost | Gradient Boosting for Additive Models | |
| boost_control | Control Hyper-parameters for Boosting Algorithms | |
| stabsel | Stability Selection | |
| survFit | Survival Curves for a Cox Proportional Hazards Model | |
| plot | Plot effect estimates of boosting models | |
| methods | Methods for Gradient Boosting Objects | |
| glmboost | Gradient Boosting with Component-wise Linear Models | |
| mboost_fit | Model-based Gradient Boosting | |
| mboost-package | mboost: Model-Based Boosting | |
| mboost_intern | Call internal functions. | |
| varimp | Variable Importance | |
| No Results! | ||
Vignettes of mboost
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Details
| Date | 2020-12-09 |
| LazyData | yes |
| License | GPL-2 |
| BugReports | https://github.com/boost-R/mboost/issues |
| URL | https://github.com/boost-R/mboost |
| NeedsCompilation | yes |
| Packaged | 2020-12-10 08:19:54 UTC; hothorn |
| Repository | CRAN |
| Date/Publication | 2020-12-10 09:40:02 UTC |
| suggests | BayesX , fields , gbm , kangar00 , MASS , mlbench , nnet , randomForest , RColorBrewer , rpart (>= 4.0-3) , testthat (>= 0.10.0) , TH.data |
| imports | graphics , grDevices , lattice , Matrix , nnls , partykit (>= 1.2-1) , quadprog , splines , survival , utils |
| depends | methods , parallel , R (>= 3.2.0) , stabs (>= 0.5-0) , stats |
| Contributors | Thomas Kneib, Peter Buehlmann, Fabian Scheipl, Benjamin Hofner, Andreas Mayr, Matthias Schmid, Fabian Otto-Sobotka |
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