但AUC有一个更优雅的，概率学上的意义：随机选取一个正例和一个负例，分类器给正例的打分大于分类器...
Learn how to evaluate your model using the AUC ROC curve in machine learning. Understand the concept and visualize classifier performance.
除了ROC曲线可以计算AUC之外,PR曲线也可以有类似的AUC计算,本文所述AUC特指AUC-ROC。一般来说,PR曲线中的precision和recall是一对trade off(互相平衡,此消彼长的),可以想象,如果对正样本,模型只成功预测出1个,并且预测对了,那么precision是100%,因为还有其他的正样本没有被发现,故recall比较低。相反,recall高了,...
This post has focused on the value and interpretation of the U statistic itself, but we have not discussed the U test, which uses this statistic (along with sample sizes) to evaluate statistical significance. According to Wikipedia, the U test evauates the null hypothesis that it is “equall...
Under geometric interpretation, if all data comes from the same class, the curve may go either straight right or straight up, depending upon the class, so it can be either 0 or 1 (or 0.5), not (necessarily) 0.0. Under statistical interpretation, the AUC is undefined. AUC isthe probabilit...
python evaluation pytorch auc roc-curve mae salient-object-detection co-saliency average-precision f-measure mean-absolute-error pr-curve e-measure s-measure Updated Dec 12, 2020 Python alvarouc / polyssifier Star 68 Code Issues Pull requests run a multitude of classifiers on you data and...
This post has focused on the value and interpretation of theU statisticitself, but we have not discussed theU test, which uses this statistic (along with sample sizes) to evaluate statistical significance. According toWikipedia, the U test evauates the null hypothesis that it is “equally like...
What is PR Curve and how to actually use it? If my problem is highly imbalanced should I use ROC AUC or PR AUC? As always it depends, but understanding the trade-offs between different metrics is crucial when it comes to making the correct decision. ...
Lastly, note that PR_AUC changes drastically if the ratio of pos:neg changes too much, given that PR_AUC is so sensitive to number of positive classes in the test set (dominating the curve). You will want to stabilize the test set pos:neg ratio else it will be misleading to think you...
首先，在试图弄懂AUC和ROC曲线之前，一定，一定要彻底理解混淆矩阵的定义！！！混淆矩阵中有着Positive、...