elastic-net-feature-selection
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.
What is this resource?
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.
Review the original project for installation steps, licenses, compatibility and updates. This directory provides discovery links, not downloadable or verified code.
Installation
For repositories supported by the Skills CLI, you can typically start with:
npx skills add aipoch/medical-research-skillsCheck the repository instructions and select the intended skill before installing. This command may not apply to every source.
Safety & attribution
This is an external resource, not independently security-audited by this directory. Inspect permissions, scripts and changes before using it with your files or accounts.