SurvivalClusteringTree
Clustering Analysis Using Survival Tree and Forest Algorithms
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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.1.3 |
rolling linux/jammy R-4.5 | SurvivalClusteringTree_1.1.3.tar.gz |
283.6 KiB |
1.1.3 |
rolling linux/noble R-4.5 | SurvivalClusteringTree_1.1.3.tar.gz |
285.9 KiB |
1.1.3 |
rolling source/ R- | SurvivalClusteringTree_1.1.3.tar.gz |
176.0 KiB |
1.1.3 |
latest linux/jammy R-4.5 | SurvivalClusteringTree_1.1.3.tar.gz |
283.6 KiB |
1.1.3 |
latest linux/noble R-4.5 | SurvivalClusteringTree_1.1.3.tar.gz |
285.9 KiB |
1.1.3 |
latest source/ R- | SurvivalClusteringTree_1.1.3.tar.gz |
176.0 KiB |
1.1.3 |
2026-04-26 source/ R- | SurvivalClusteringTree_1.1.3.tar.gz |
176.0 KiB |
1.1.3 |
2026-04-23 source/ R- | SurvivalClusteringTree_1.1.3.tar.gz |
176.0 KiB |
1.1.3 |
2026-04-09 windows/windows R-4.5 | SurvivalClusteringTree_1.1.3.zip |
603.0 KiB |
1.1.1 |
2025-04-20 source/ R- | SurvivalClusteringTree_1.1.1.tar.gz |
175.4 KiB |