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SurvivalClusteringTree  

Clustering Analysis Using Survival Tree and Forest Algorithms
View on CRAN: Click here


Download and install SurvivalClusteringTree package within the R console
Install from CRAN:
install.packages("SurvivalClusteringTree")

Install from Github:
library("remotes")
install_github("cran/SurvivalClusteringTree")

Install by package version:
library("remotes")
install_version("SurvivalClusteringTree", "1.1.1")



Attach the package and use:
library("SurvivalClusteringTree")
Maintained by
Lu You
[Scholar Profile | Author Map]
First Published: 2023-09-11
Latest Update: 2023-09-11
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>.
How to cite:
Lu You (2023). SurvivalClusteringTree: Clustering Analysis Using Survival Tree and Forest Algorithms. R package version 1.1.1, https://cran.r-project.org/web/packages/SurvivalClusteringTree. Accessed 01 May. 2025.
Previous versions and publish date:
1.0 (2023-09-11 10:40), 1.1 (2024-05-13 22:33)
Other packages that cited SurvivalClusteringTree R package
View SurvivalClusteringTree citation profile
Other R packages that SurvivalClusteringTree depends, imports, suggests or enhances
Complete documentation for SurvivalClusteringTree
Functions, R codes and Examples using the SurvivalClusteringTree R package
Full SurvivalClusteringTree package functions and examples
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