| Name : R-piRF
| |
| Version : 0.1.0
| Vendor : obs://build_opensuse_org/devel:languages:R
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| Release : lp153.4.13
| Date : 2024-06-14 11:31:10
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| Group : Development/Libraries/Other
| Source RPM : R-piRF-0.1.0-lp153.4.13.src.rpm
|
| Size : 0.13 MB
| |
| Packager : (none)
| |
| Summary : Prediction Intervals for Random Forests
|
Description :
Implements multiple state-of-the-art prediction interval methodologies
for random forests. These include: quantile regression intervals,
out-of-bag intervals, bag-of-observations intervals, one-step boosted
random forest intervals, bias-corrected intervals, high-density
intervals, and split-conformal intervals. The implementations include a
combination of novel adjustments to the original random forest
methodology and novel prediction interval methodologies. All of these
methodologies can be utilized using solely this package, rather than a
collection of separate packages. Currently, only regression trees are
supported. Also capable of handling high dimensional data. Roy,
Marie-Helene and Larocque, Denis (2019) < doi:10.1177/0962280219829885>.
Ghosal, Indrayudh and Hooker, Giles (2018) < arXiv:1803.08000>. Zhu, Lin
and Lu, Jiaxin and Chen, Yihong (2019) < arXiv:1905.10101>. Zhang,
Haozhe and Zimmerman, Joshua and Nettleton, Dan and Nordman, Daniel J.
(2019) < doi:10.1080/00031305.2019.1585288>. Meinshausen, Nicolai (2006)
< http://www.jmlr.org/papers/volume7/meinshausen06a/meinshausen06a.pdf>.
Romano, Yaniv and Patterson, Evan and Candes, Emmanuel (2019)
< arXiv:1905.03222>. Tung, Nguyen Thanh and Huang, Joshua Zhexue and
Nguyen, Thuy Thi and Khan, Imran (2014) < doi:10.13140/2.1.2500.8002>.
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RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
