召回率与精度图 [英] recall vs precision graph

问题描述

我正在尝试绘制精度与召回率的图表，这是我的分类报告.我不知道如何绘制显示这些的图表.这是我的分类报告代码

I'm trying to plot a graph for precision vs recall this is my classification report. i don't know how to plot a graph displaying these. this is my code for classification report

from sklearn.metrics import classification_report
print("")
print("Confusion Matrix")
print(confusion_matrix(Y_test, predictions))
print("")
print("Classification Report                                XGBOOST")
print(classification_report(predictions,Y_test))

输出:

Confusion Matrix
[[1163   55]
 [  46  665]]

Classification Report                                 xgboost
              precision    recall  f1-score   support

           0       0.95      0.96      0.96      1209
           1       0.94      0.92      0.93       720

    accuracy                           0.95      1929
   macro avg       0.95      0.94      0.94      1929
weighted avg       0.95      0.95      0.95      1929

我正在尝试做这样的事情:

i'm trying to do something like this:

使用图表显示我的精确度和召回率.

visulise my precision and recall using a graph.

推荐答案

from sklearn.metrics import precision_recall_curve
precision, recall, thresholds = precision_recall_curve(Y_test,predictions)
plt.step(recall, precision, color='b', alpha=0.2,
         where='post')
plt.fill_between(recall, precision, alpha=0.2, color='b')
plt.xlabel('Recall')
plt.ylabel('Precision')
plt.ylim([0.0, 1.05])
plt.xlim([0.0, 1.0])

试试这个.

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