xgb-deepmodel
xgb-deepmodel is a Model training & evaluation skill for AI agents, published by aliyun in the qwen-dianjin repository on GitHub. Skillspace rates xgb-deepmodel C (71/100) and it passed the safety scan; the rating is based on static analysis only.
【DeepModel深度建模】当用户需要"分群集成建模"、"分群+Stacking融合"、"子模型训练+集成"时使用。核心能力：按业务分群条件训练多个 XGBoost 子模型，通过 Stacking 融合成主模型，并与单模型基线对比。适用于"分群建模"、"按客群分别建模"、"子模型融合"、"集成学习"等高级场景。包含三个脚本：sub_trainer（分群子模型训练）、stacker（XGBoost Stacking融合）、comparator（集成vs基线对比）。与 xgb-modeling 的区别：本 Skill 拆分客群分别建模再融合，xgb-modeling 全量样本统一建模。与 segment-modeling 的区别：本 Skill 专注分群+Stacking融合，segment-modeling 专注分群策略探索。
- Grade
- C
- Quality
- 71 / 100
- Safety
- Passed
- GitHub stars
- 571
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 94 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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