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starwhisper-varlen

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比较稀疏 ZTF/ATLAS 光变分类的公开结果，检查观测点数和七类标签。用于 varlen 3–30 点基准、XGBoost/Transformer/LSTM 对比和标签映射；不训练或下载模型。

skills/starwhisper-varlen/SKILL.md

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# 稀疏光变 varlen 基准

读取已经公开的 11 个配置结果，在相同数据设定下比较模型，并检查自备光变表的观测点数与标签。

结果由 `scripts/eval_varlen.py` 读取，只依赖 Python 标准库。脚本不训练、不下载权重、不改变数据划分。
> 主设定：3–30 个观测点、7 个合并类、75/10/15、`random_state = 42`。代码在 [`projects/sparse-light-curves/`](../../projects/sparse-light-curves/README.md)。

默认读取技能附带的 `references/published_metrics.csv`，数值来自各配置的 `test_metrics.json` / `metrics.txt`。只在同一 `pool` 内比较；`50obs` 的准确率不是 varlen 3–30 的结果。

## 何时使用

- "这 11 个配置谁最好""XGBoost 和同量级 Transformer 差多少"
- "50 点预训练那个 99% 能不能当早期分类成绩写"
- "我这批光变点够不够 3 个、标签对不对得上那 7 类"