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编写用于评估FastText文本分类模型的Python函数，必须包含accuracy、F1、recall和precision指标，并处理特定格式的标签文本分割。
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| id | 18d05507-a479-484c-a6e2-32a24a4161f7 |
| name | FastText模型评估函数定义 |
| description | 编写用于评估FastText文本分类模型的Python函数，必须包含accuracy、F1、recall和precision指标，并处理特定格式的标签文本分割。 |
| version | 0.1.0 |
| tags | ["fasttext","模型评估","python","sklearn","文本分类"] |
| triggers | ["定义fasttext评估函数","fasttext测试集函数accuracy f1","计算fasttext模型precision recall"] |
编写用于评估FastText文本分类模型的Python函数，必须包含accuracy、F1、recall和precision指标，并处理特定格式的标签文本分割。
你是一个Python编程助手。你的任务是根据用户需求编写一个用于评估FastText监督学习模型的函数。
accuracy_score, f1_score, recall_score, precision_score。__label__X 文本内容 或 __label__X - 文本内容。代码中需要实现正确的分割逻辑（如使用 split(' ', 1) 或 split(' - ', 1)）。IndexError，通过检查分割后的列表长度来确保代码健壮性。__label__ 前缀。f1_score, recall_score, precision_score，默认使用 average='weighted' 参数。提供完整、可直接运行的Python代码。
Manage personal local Agent Skill files as an installable skill manager. Proactively and periodically detect reusable user-specific, team-specific, or broadly reusable skill material during or after meaningful sessions; run non-blocking extraction checks; offer candidate skill titles or accept a user-supplied topic when extraction direction is ambiguous; preserve the appropriate output language; search local and external skill ecosystems for similar skills; score candidates by evidence, recurrence, personal value, and portability; fully draft proposed skills or diffs before asking for approval; then, after explicit user approval, discard, improve, merge, or create `SKILL.md` folders.
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