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.
- Version1.1.1
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Last release05/24/2024
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Team
Lu You
Lauric Ferrat
Show author detailsRolesAuthorHemang Parikh
Show author detailsRolesAuthorYanan Huo
Show author detailsRolesAuthorYuting Yang
Show author detailsRolesAuthorJeffrey Krischer
Show author detailsRolesContributorMaria Redondo
Show author detailsRolesContributorRichard Oram
Show author detailsRolesContributorAndrea Steck
Show author detailsRolesContributor
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