我无法绘制以下数据：(查准率-回忆曲线)

Question

嗨，我试图用下列数据绘制召回-精确曲线：

      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

源代码：

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()

AUC = 0.01的面积是正常的吗？

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Answer 1

这似乎是正确的答案。

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