Python中ROC曲线绘制

from sklearn.svm import SVC
from sklearn.metrics import roc_curve
from sklearn.datasets import make_blobs
from sklearn. model_selection import train_test_split
import matplotlib.pyplot as plt
%matplotlib inline

X,y = make_blobs(n_samples=(4000,500), cluster_std=[7,2], random_state=0)
 
X_train,X_test,y_train, y_test = train_test_split(X,y,random_state=0)
 
clf = SVC(gamma=0.05).fit(X_train, y_train)

fpr,tpr, thresholds = roc_curve(y_test,clf.decision_function(X_test))
 
plt.plot(fpr,tpr,label='ROC')
 
plt.xlabel('FPR')
plt.ylabel('TPR')

fpr,tpr, thresholds = roc_curve(y_test,clf.predict_proba(X_test)[:,1])
 
 
plt.plot(fpr,tpr,label='ROC')
 
plt.xlabel('FPR')
plt.ylabel('TPR')