| Name : R-vip
| |
| Version : 0.4.1
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : 2.9
| Date : 2024-08-05 21:12:16
|
| Group : Development/Libraries/Other
| Source RPM : R-vip-0.4.1-2.9.src.rpm
|
| Size : 3.14 MB
| |
| Packager : (none)
| |
| Summary : Variable Importance Plots
|
Description :
A general framework for constructing variable importance plots from
various types of machine learning models in R. Aside from some standard
model- specific variable importance measures, this package also
provides model- agnostic approaches that can be applied to any
supervised learning algorithm. These include 1) an efficient
permutation-based variable importance measure, 2) variable importance
based on Shapley values (Strumbelj and Kononenko, 2014)
< doi:10.1007/s10115-013-0679-x>, and 3) the variance-based approach
described in Greenwell et al. (2018) < arXiv:1805.04755>. A
variance-based method for quantifying the relative strength of
interaction effects is also included (see the previous reference for
details).
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/x86_64 |
