如何使用 scikit learn 或任何其他 python 库为 csv 文件绘制 roc 曲线,如下所示:
1, 0.202
0, 0.203
0, 0.266
1, 0.264
0, 0.261
0, 0.291
.......
最佳答案
import pandas as pd
import numpy as np
import pylab as pl
from sklearn.metrics import roc_curve, auc
df = pd.read_csv('filename.csv')
y_test = np.array(df)[:,0]
probas = np.array(df)[:,1]
# Compute ROC curve and area the curve
fpr, tpr, thresholds = roc_curve(y_test, probas)
roc_auc = auc(fpr, tpr)
print("Area under the ROC curve : %f" % roc_auc)
# Plot ROC curve
pl.clf()
pl.plot(fpr, tpr, label='ROC curve (area = %0.2f)' % roc_auc)
pl.plot([0, 1], [0, 1], 'k--')
pl.xlim([0.0, 1.0])
pl.ylim([0.0, 1.0])
pl.xlabel('False Positive Rate')
pl.ylabel('True Positive Rate')
pl.title('Receiver operating characteristic')
pl.legend(loc="lower right")
pl.show()
关于python - csv 文件中的 RoC 曲线,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/23130259/