[英]python - Plot Precision Recall Curve for different multi-class classifiers
I have predicted output for validation data which is single label multi-class classifier.我已经预测了验证数据的输出,它是单标签多类分类器。 I have run multiple classifiers.
我已经运行了多个分类器。 I want to plot the PR curves for each of them in a single plot.
我想在一个图中为每个人绘制 PR 曲线。 I am not able to do that.
我不能那样做。 Any pointers?
任何指针?
For a single classifier, the dataframe with results look like this :
label predictedAns predictedProb
1 2 0.999281
2 2 0.999754
2 2 0.999754
3 3 0.999762
2 2 0.999641
2 2 0.999641
2 2 0.9996
You can seperately calculate metrics you want to observe for different cutoffs, and then refer to this page later on.您可以针对不同的临界值分别计算要观察的指标,然后稍后参考此页面。 Plotly comes with handy notebook integration, as interactive plots.
Plotly 带有方便的笔记本集成,作为交互式绘图。 You can add different lines with "add_trace" method which you can find it on the page, and observe all of them in a single interactive plot.
您可以使用“add_trace”方法添加不同的行,您可以在页面上找到它,并在单个交互式图中观察所有这些行。
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