已有 successful S-Learner 或 T-Learner modeling_result_path 后，用于生成、确认并执行有边界的 LightGBM learner 调参 study。不要用于首次训练、多模型比较、最终报告或模型采用决策。
How to install uplift-model-tuning?
qfin-tech/model-evo/uplift-model-tuning
$npx -y skills add qfin-tech/model-evo --skill uplift-model-tuningInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/qfin-tech/model-evo" --skill "qfin-tech/model-evo/uplift-model-tuning"` 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/qfin-tech/model-evo" that are relevant to the current task. Run `npx skills add "https://github.com/qfin-tech/model-evo"` and select the relevant skills, then follow their instructions.
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