Description
Autoencoding Random Forests ('RFAE') provide a method to autoencode mixed-type tabular data using Random Forests ('RF'), which involves projecting the data to a latent feature space of user-chosen dimensionality (usually a lower dimension), and then decoding the latent representations back into the input space. The encoding stage is useful for feature engineering and data visualisation tasks, akin to how principal component analysis ('PCA') is used, and the decoding stage is useful for compression and denoising tasks. At its core, 'RFAE' is a post-processing pipeline on a trained random forest model. This means that it can accept any trained RF of 'ranger' object type: 'RF', 'URF' or 'ARF'. Because of this, it inherits Random Forests' robust performance and capacity to seamlessly handle mixed-type tabular data. For more details, see Vu et al. (2025) <doi:10.48550/arXiv.2505.21441>.
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| Flavor | Status |
|---|---|
| r-devel-linux-x86_64-debian-clang | OK |
| r-devel-linux-x86_64-debian-gcc | OK |
| r-devel-linux-x86_64-fedora-clang | OK |
| r-devel-linux-x86_64-fedora-gcc | OK |
| r-devel-windows-x86_64 | OK |
| r-oldrel-macos-arm64 | OK |
| r-oldrel-macos-x86_64 | OK |
| r-oldrel-windows-x86_64 | OK |
| r-patched-linux-x86_64 | OK |
| r-release-linux-x86_64 | OK |
| r-release-macos-arm64 | OK |
| r-release-macos-x86_64 | OK |
| r-release-windows-x86_64 | OK |
Check History
OK 13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Jun 9, 2026
ERROR 12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE Jun 8, 2026
package dependencies
Package required but not available: ‘caret’ See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’ manual.
OK 13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE May 2, 2026
ERROR 11 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE Apr 25, 2026
package dependencies
Package required but not available: ‘caret’ See section ‘The DESCRIPTION file’ in the ‘Writing R Extensions’ manual.
OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026
Dependency Network
Version History
1 trackedR Observatory began tracking this package on Mar 10, 2026; it first appeared on CRAN Jan 17, 2026. Releases before tracking aren’t shown.