> For the complete documentation index, see [llms.txt](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://baozoulin.gitbook.io/neural-networks-and-deep-learning/di-san-men-ke-jie-gou-hua-ji-qi-xue-xi-xiang-mu-structuring-machine-learning-projects/di-san-men-ke-structuring-machine-learning-projects/di-yi-zhou-ml-strategy/13-dan-yi-shu-zi-ping-gu-zhi-biao-ff08-single-number-evaluation-metric.md).

# 1.3 单一数字评估指标（Single number evaluation metric）

A和B模型的准确率（Precision）和召回率（Recall）分别如下：

![](https://2314428465-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-Le0cHhI0S0DK8pwlrmD%2F-Le0cKOp1vaxoORIi4ak%2F-Le0ctehu1wnp9KH2Nod%2Fimport.png310?generation=1556953145835791\&alt=media)

使用单值评价指标F1 Score来评价模型的好坏。F1 Score综合了Precision和Recall的大小：

$$
F1=\frac{2\cdot P\cdot R}{P+R}
$$

![](https://2314428465-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-Le0cHhI0S0DK8pwlrmD%2F-Le0cKOp1vaxoORIi4ak%2F-Le0ctelpcunwweSaQG3%2Fimport.png302?generation=1556953144832093\&alt=media)

还可以使用平均值作为单值评价指标：

![](https://2314428465-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-Le0cHhI0S0DK8pwlrmD%2F-Le0cKOp1vaxoORIi4ak%2F-Le0ctenHcgQQjIwyWHq%2Fimport.png303?generation=1556953145028557\&alt=media)

> 不同国家样本的错误率，计算平均性能，选择平均错误率最小的模型（C模型）

![](https://2314428465-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-Le0cHhI0S0DK8pwlrmD%2F-Le0cKOp1vaxoORIi4ak%2F-Le0ctepKY_5eeNDBks_%2F326import.png?generation=1556953145046666\&alt=media)![](https://2314428465-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-Le0cHhI0S0DK8pwlrmD%2F-Le0cKOp1vaxoORIi4ak%2F-Le0cterLbgNPEnNSc-T%2F329import.png?generation=1556953144892256\&alt=media)