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kmeans

Business
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使用 K-Means 对业务对象进行聚类画像

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Source SKILL.md: https://github.com/Zafer-Liu/Data-Analysis-Agent/blob/HEAD/skills/kmeans/SKILL.md

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K-Means 聚类

确认聚类实体与特征，处理缺失值并标准化数值变量。比较合理的 K 值，报告聚类质量、各簇规模、中心特征和业务画像，并说明异常点及稳定性限制。

Tool routing

  1. Use get_schema to identify the entity key, candidate numeric features, and source table.
  2. Use query_data to verify feature availability, missingness, and scale before modeling.
  3. Use run_analysis with analysis_name="K_Means" for the clustering computation.
  4. Use generate_chart on cluster profiles, elbow output, or label result tables after run_analysis succeeds.

Implementation reference

  • Tool entry: agent/tools/business/data.py::_tool_run_analysis
  • Analysis registry: Function/Analyze/registry.py
  • Analysis implementation: Function/Analyze/K-Means/analyze.py
  • Chart implementation: Function/Charts_generation/chart_generate.py