SurvivalClusteringTree
Clustering Analysis Using Survival Tree and Forest Algorithms
Description
An outcome-guided algorithm is developed to identify clusters of samples with similar characteristics and survival rate. The algorithm first builds a random forest and then defines distances between samples based on the fitted random forest. Given the distances, we can apply hierarchical clustering algorithms to define clusters. Details about this method is described in <https://github.com/luyouepiusf/SurvivalClusteringTree>.
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CRAN Check Status
Show all 13 flavors
| 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 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Apr 22, 2026
ERROR 13 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE Apr 18, 2026
whether package can be installed
Installation failed. See 'd:/Rcompile/CRANpkg/local/4.6/SurvivalClusteringTree.Rcheck/00install.out' for details.