auc

AUC的音标是/əʊtʃ/，基本翻译为“上限”、“最高点”，速记技巧可以考虑谐音记忆，将其与“奥数”相联系进行记忆。

AUC这个词的英文词源可以追溯到拉丁语“audire”和“crescere”，意为“听”和“生长”。它的变化形式包括“auximus”和“audax”，前者表示“我们听到了”，后者表示“大胆的，勇敢的”。

相关单词：

1. Audacity - 勇敢，大胆，无畏

2. Audition - 试听，试奏

3. Auditory - 听觉的

4. Accuracy - 准确度

5. Audacious - 英勇的，大胆的

6. Audit - 审计，检查

7. Audiovisual - 视听

8. Audiophile - 音响爱好者

9. Audience - 观众，听众

10. Assurance - 信心，担保

AUC这个词在医学和机器学习领域中经常使用，用于评估预测模型的性能，特别是在分类问题中。它可以帮助我们理解模型的泛化能力，即在未见过的数据上表现的能力。

AUC（Area Under the Curve）常用短语：

1. AUC值大于0.7表示模型表现良好。

2. AUC值越接近1，模型表现越好。

双语例句：

1. The model achieved an AUC of 0.9, indicating excellent performance.

2. The results show that the proposed model outperforms the baseline by a significant margin with an AUC of 0.85.

英文小作文：

Title: AUC Analysis of a Machine Learning Model

AUC（Area Under the Curve）is a metric commonly used in machine learning to evaluate the performance of a binary classification model. When the AUC value is above 0.7, it indicates that the model performs well, and the closer the value is to 1, the better the performance of the model.

In this analysis, we applied a machine learning model to a dataset and obtained an AUC value of 0.9. This indicates that the model performed extremely well and was able to correctly classify most of the samples. In comparison, a baseline model only achieved an AUC of 0.7, indicating that the proposed model outperformed the baseline significantly.

Through this analysis, we can see that AUC is a valuable metric to evaluate the performance of a binary classification model, and it can help us identify which models perform better and which ones can be safely discarded.