import matplotlib.pyplot as plt
from sklearn.metrics import roc_curve, auc,recall_score,precision_score

fpr, tpr, _ = roc_curve(y_test, pred)
roc_auc = auc(fpr, tpr)
plt.figure()
lw = 2
plt.plot(fpr, tpr, color='orange',
         lw=lw, label='AUC = %0.4f' % roc_auc)
plt.plot([0, 1], [0, 1], color='steelblue', lw=lw, linestyle='--')
plt.xlim([-0.02, 1.0])
plt.ylim([0.0, 1.05])
plt.xlabel('False Positive Rate')
plt.ylabel('True Positive Rate')
plt.title('ROC curve')
plt.legend(loc="lower right")
plt.show()