SurvivalClusteringTree
1.1.3Clustering Analysis Using Survival Tree and Forest Algorithms
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Overview
About
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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9 external dependencies (excludes base and recommended)
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Rcppsurvivaldplyrgridformula.tools
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Package metadata
- First published
- 2023-09-11
- Total releases
- 4 / 3 yrs
- License
- GPL (>= 2) OSI
- Download size
- 175 KB
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- not tracked yet