關于auc和f1的選擇

In general, the ROC is used for many different levels of thresholds and thus it has many F score values. F1 score is applicable for any particular point on the ROC curve.

You may think of it as a measure of precision and recall at a particular threshold value whereas AUC is the area under the ROC curve. For F score to be high, both precision and recall should be high.

When you have a data imbalance between positive and negative samples, you should always use F1-score because of ROC averages over all possible thresholds.

?著作權歸作者所有,轉載或內容合作請聯系作者
平臺聲明：文章內容（如有圖片或視頻亦包括在內）由作者上傳并發布，文章內容僅代表作者本人觀點，簡書系信息發布平臺，僅提供信息存儲服務。