svm-models
Survival Support Vector Machines (SVMs) adapt the traditional SVM framework to survival analysis with censored data. They optimize a ranking objective that encourages correct ordering of survival times.
- Skills
- Scientific
- 0
What it does and how to use it
A skill that teaches Claude Code to do scientific tasks well. It is packaged knowledge the model uses whenever it is relevant.
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Install (Claude Code)
mkdir -p .claude/skills/svm-models && curl -fsSL https://doutorai.pt/data/lib/skills__svm-models.md -o .claude/skills/svm-models/SKILL.mdPaste this command into the terminal, in your project folder, and the component installs automatically.
Content
# Survival Support Vector Machines
## Overview
Survival Support Vector Machines (SVMs) adapt the traditional SVM framework to survival analysis with censored data. They optimize a ranking objective that encourages correct ordering of survival times.
### Core Idea
SVMs for survival analysis learn a function f(x) that produces risk scores, where the optimization ensures that subjects with shorter survival times receive higher risk scores than those with longer times.
## When to Use Survival SVMs
**Appropriate for:**
- Medium-sized datasets (typically 100-10,000 samples)
- Need for non-line
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