varSelRF
Variable Selection using Random Forests
Variable selection from random forests using both backwards variable elimination (for the selection of small sets of non-redundant variables) and selection based on the importance spectrum (somewhat similar to scree plots; for the selection of large, potentially highly-correlated variables). Main applications in high-dimensional data (e.g., microarray data, and other genomics and proteomics applications).
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.7-9 |
rolling linux/jammy R-4.5 | varSelRF_0.7-9.tar.gz |
113.9 KiB |
0.7-9 |
rolling linux/noble R-4.5 | varSelRF_0.7-9.tar.gz |
113.9 KiB |
0.7-9 |
rolling source/ R- | varSelRF_0.7-9.tar.gz |
28.7 KiB |
0.7-9 |
latest linux/jammy R-4.5 | varSelRF_0.7-9.tar.gz |
113.9 KiB |
0.7-9 |
latest linux/noble R-4.5 | varSelRF_0.7-9.tar.gz |
113.9 KiB |
0.7-9 |
latest source/ R- | varSelRF_0.7-9.tar.gz |
28.7 KiB |
0.7-9 |
2026-04-26 source/ R- | varSelRF_0.7-9.tar.gz |
28.7 KiB |
0.7-9 |
2026-04-23 source/ R- | varSelRF_0.7-9.tar.gz |
28.7 KiB |
0.7-9 |
2026-04-09 windows/windows R-4.5 | varSelRF_0.7-9.zip |
116.4 KiB |
0.7-8 |
2025-04-20 source/ R- | varSelRF_0.7-8.tar.gz |
28.1 KiB |