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).
copied from cf-staging / r-varselrf| Label | Latest Version |
|---|---|
| main | 0.7_8 |
| cf201901 | 0.7_8 |
| cf202003 | 0.7_8 |
| gcc7 | 0.7_8 |
