f1 f3score

F和F3分数是量分类模型性能的指标。F1分数是准确率和召回率的调和平均值，用于衡量模型的精确性和完整性。F3分数是准确率和召回率的调和平均值，但召回率的权重更高，用于更加关注模型的召回率。

F1分数可以使用以下公式计算：<span class="em">1</span><span class="em">2</span><span class="em">3</span>
#### 引用[.reference_title]
- *1* [机器学习-多分类的性能评价指标及其含义（查全率、查准率、F1-score、混淆矩阵）](https://blog.csdn.net/u011503666/article/details/108267692)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v92^chatsearchT3_1"}}] [.reference_item style="max-width: 50%"]
- *2* *3* [f1 score sklearn中 F1-micro 与 F1-macro区别和计算原理](https://blog.csdn.net/jacke121/article/details/128945444)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v92^chatsearchT3_1"}}] [.reference_item style="max-width: 50%"]
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