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SurvivalClusteringTree

Clustering Analysis Using Survival Tree and Forest Algorithms

v1.1.3 · Feb 24, 2026 · GPL (>= 2)

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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r-release-windows-x86_64 OK
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OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026

Dependency Network

Dependencies Reverse dependencies Rcpp survival dplyr formula.tools SurvivalClusteringTree

Version History

new 1.1.3 Mar 9, 2026