elastic-net-feature-selection
byaipoch· 77 skills
Use when selecting predictive genes or other molecular features from bulk expression matrices for binary case-vs-control classification with elastic net logistic regression, including coefficient path and cross-validation plots. Trigger keywords: elastic net, glmnet, feature selection, binary classification, lambda.min, lambda.1se. NOT for: survival/Cox modeling, multiclass outcomes, single-cell data, or non-expression tables.
How to install elastic-net-feature-selection?
aipoch/medical-research-skills/elastic-net-feature-selection
$npx -y skills add aipoch/medical-research-skills --skill elastic-net-feature-selectionInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/aipoch/medical-research-skills" --skill "aipoch/medical-research-skills/elastic-net-feature-selection"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/aipoch/medical-research-skills" that are relevant to the current task. Run `npx skills add "https://github.com/aipoch/medical-research-skills"` and select the relevant skills, then follow their instructions.
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