# Tree

> 使用决策树识别影响目标变量的关键规则（decision tree 决策树）

- Skill: `zafer-liu/tree` (Agent Skill)
- Install (CLI): `npx skillmds add zafer-liu/tree`
- Raw SKILL.md: https://api.skillmd.com/api/skills/zafer-liu/tree/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: Zafer-Liu (https://skillmd.com/u/zafer-liu)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/zafer-liu/tree

---

# 决策树分析

确认目标变量和任务类型，排除泄漏字段，合理处理缺失值与类别变量。执行训练验证并报告性能、重要特征和可解释规则；避免把相关性表述为因果。

## Tool routing

1. Use `get_schema` to identify the target, candidate features, task type, and source table.
2. Use `query_data` to verify field names, target distribution, missingness, and leakage risks.
3. Use `run_analysis` with `analysis_name="Decision_Tree"` for the actual tree computation.
4. Use `generate_chart` on tree, feature importance, or validation 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/Decision_Tree/analyze.py`
- Chart implementation: `Function/Charts_generation/chart_generate.py`