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Signed-off-by: Raphael Sonabend <raphaelsonabend@gmail.com>
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Sep 15, 2025
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some minor stuff only
| This chapter starts with SVMs in the regression setting before moving to adaptions for survival analysis. | ||
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| As of the time of publication, no SSVMs for competing risks appear to have been published [@Kantidakis2023; @Monterrubio-Gómez2024; @Djangang2025]. | ||
| Theoretically, one could use any of the methods to estimate per-cause risk by considering each risk separately and censoring observations that experience a different risk, however this has not been validated in the literature. |
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the important part in the caus-specific paradigm is that the learner returns a hazard estimate. If thats the case, you can calculate the CIF. If it only returns the surv prob, one could try to approximate a hazard estimate from S(t) (e.g. via numeric differentiation and some assumptions), but it's less common. not sure if SVM provides hazard estimates
Signed-off-by: Raphael Sonabend <raphaelsonabend@gmail.com>
Signed-off-by: Raphael Sonabend <raphaelsonabend@gmail.com>
Signed-off-by: Raphael Sonabend <raphaelsonabend@gmail.com>
Signed-off-by: Raphael Sonabend <raphaelsonabend@gmail.com>
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Signed-off-by: Raphael Sonabend <raphaelsonabend@gmail.com>
Signed-off-by: Raphael Sonabend <raphaelsonabend@gmail.com>
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