SurvivalClusteringTree

cranv1.1.3

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

License GPL (>= 2)0 versions1 maintainers5 deps60 weekly dl
https://CRAN.R-project.org/package=SurvivalClusteringTree
47
/ 100
Health
safe to use

[email protected] is safe to use (health: 47/100)

Health breakdown0 – 100
20/25
maintenance
0/20
popularity
25/25
security
0/15
maturity
2/15
community
Vulnerabilities
0
none known

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First published · 2026-02-25 06:44:34

Last updated · 2026-02-25T05:10:02+00:00

SurvivalClusteringTree — Health Score 47/100 | DepScope