Installation
About
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.
Citation | mboost citation info |
github.com/boost-R/mboost | |
Bug report | File report |
Key Metrics
Downloads
Yesterday | 333 0% |
Last 7 days | 860 -16% |
Last 30 days | 4.410 -11% |
Last 90 days | 17.233 +4% |
Last 365 days | 62.829 -15% |