我不能繪製以下數據：（精確召回曲線）

Question

你好我試圖通過使用下面的數據來繪製召回精密曲線：

 Recall Precision 
0.88196 0.467257 
0.898501 0.468447 
0.89899 0.470659 
0.900789 0.471653 
0.900922 0.472038 
0.901012 0.472359 
0.901345 0.480144 
0.901695 0.482353 
0.902825 0.482717 
0.903261 0.483125 
0.905152 0.483621 
0.905575 0.485088 
0.905682 0.486339 
0.906109 0.488117 
0.906466 0.488459 
0.90724 0.488587 
0.908989 0.488875 
0.909941 0.489362 
0.910125 0.489493 
0.910314 0.490196 
0.910989 0.49022 
0.91106 0.490786 
0.911137 0.496624 
0.91129 0.496891 
0.911392 0.497301 
0.911392 0.499379 
0.911422 0.5 
0.911452 0.503783 
0.911525 0.515829 

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的源代碼：

import random 
import pylab as pl 
from sklearn import svm, datasets 
from sklearn.metrics import precision_recall_curve 
from sklearn.metrics import auc 

##Load Recall 
fname = "recall.txt" 
fname1 = "precision.txt" 

recall = [] 
precision = [] 

with open(fname) as inf: 
    for line in inf: 
     recall.append(float(line)) 

with open(fname1) as inf: 
    for line in inf: 
     precision.append(float(line)) 

area = auc(recall, precision) 
print("Area Under Curve: %0.2f" % area) 

pl.clf() 
pl.plot(recall, precision, label='Precision-Recall curve') 
pl.xlabel('Recall') 
pl.ylabel('Precision') 
pl.ylim([0.0, 1.05]) 
pl.xlim([0.0, 1.0]) 
pl.title('Precision-Recall example: AUC=%0.2f' % area) 
pl.legend(loc="lower left") 
pl.show() 

我得到的面積在AUC = 0.01以下是正常的嗎？

Answer 1

這似乎是正確的答案。

使用numpy.trapz(precission, recall)我得到AUC = 0.014036223712000031