xgboost-analysis
Use when building XGBoost models on tabular data and returning feature importance ranking outputs. Supports binary classification and regression with automatic task detection, train-test split, performance tables, feature importance ranking tables, and PNG importance plots.
What is this resource?
Use when building XGBoost models on tabular data and returning feature importance ranking outputs. Supports binary classification and regression with automatic task detection, train-test split, performance tables, feature importance ranking tables, and PNG importance plots.
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.