使用keras绘制Roc曲线

import numpy as np
import matplotlib.pyplot as plt
from sklearn.metrics import roc_curve, auc

# 假设有真实标签y_true和模型预测概率y_pred
y_true = np.array([0, 0, 1, 1, 1])
y_pred = np.array([0.1, 0.3, 0.4, 0.6, 0.8])

fpr, tpr, thresholds = roc_curve(y_true, y_pred)

roc_auc = auc(fpr, tpr)

plt.figure()
plt.plot(fpr, tpr, color='darkorange', lw=2, label='ROC curve (area = %0.2f)' % roc_auc)
plt.plot([0, 1], [0, 1], color='navy', lw=2, linestyle='--')
plt.xlim([0.0, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.title('Receiver Operating Characteristic')
plt.legend(loc="lower right")
plt.show()