Performs support vectors analysis for data sets with survival outcome. Three approaches are available in the package: The regression approach takes censoring into account when formulating the inequality constraints of the support vector problem. In the ranking approach, the inequality constraints set the objective to maximize the concordance index for comparable pairs of observations. The hybrid approach combines the regression and ranking constraints in the same model.
Version: | 0.0.5 |
Depends: | survival |
Imports: | pracma, quadprog, kernlab, Matrix, stats, Hmisc |
Suggests: | testthat |
Published: | 2018-02-05 |
DOI: | 10.32614/CRAN.package.survivalsvm |
Author: | Cesaire J. K. Fouodo |
Maintainer: | Cesaire Fouodo <fouodo at imbs.uni-luebeck.de> |
BugReports: | https://github.com/imbs-hl/survivalsvm/issues |
License: | GPL-2 | GPL-3 [expanded from: GPL] |
URL: | https://github.com/imbs-hl/survivalsvm |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | survivalsvm results |
Reference manual: | survivalsvm.pdf |
Package source: | survivalsvm_0.0.5.tar.gz |
Windows binaries: | r-devel: survivalsvm_0.0.5.zip, r-release: survivalsvm_0.0.5.zip, r-oldrel: survivalsvm_0.0.5.zip |
macOS binaries: | r-release (arm64): survivalsvm_0.0.5.tgz, r-oldrel (arm64): survivalsvm_0.0.5.tgz, r-release (x86_64): survivalsvm_0.0.5.tgz, r-oldrel (x86_64): survivalsvm_0.0.5.tgz |
Old sources: | survivalsvm archive |
Reverse imports: | EnMCB |
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