我无法绘制以下数据：（精度-召回率曲线）

Question

你好，我想通过使用以下数据绘制召回率-精确度曲线：

      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

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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()

我得到的AUC = 0.01的面积正常吗？

- Hani Goc

Answer 1

看起来这是正确的答案。

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

- plover

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这就是我想的，@plover。谢谢，我实际上犯了一个错误。 - Hani Goc