I can't plot the following data : (Precision-Recall curve)

Question

Hi I am trying to plot the Recall-Precision curve by using the following data:

      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

---

Source code:

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()

I get the area under AUC = 0.01 is that normal?

Answer 1

It seems to be the right answer.

Using numpy.trapz(precission, recall) I get AUC = 0.014036223712000031