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
- Version2.9-11
- R version≥ 3.2.0 methods
- LicenseGPL-2
- Needs compilation?Yes
- mboost citation info
- Last release08/22/2024
Documentation
Team
Torsten Hothorn
Peter Buehlmann
Thomas Kneib
Matthias Schmid
Benjamin Hofner
Fabian Otto-Sobotka
Fabian Scheipl
Andreas Mayr
Insights
Last 30 days
Last 365 days
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Depends4 packages
- Imports9 packages
- Suggests12 packages
- Reverse Depends7 packages
- Reverse Imports13 packages
- Reverse Suggests17 packages