1.py 文件源码

def Precision(clf):
    doc_class_predicted = clf.predict(x_test) 
    print(np.mean(doc_class_predicted == y_test))#?????????
    #???????  
    precision, recall, thresholds = precision_recall_curve(y_test, clf.predict(x_test))  
    answer = clf.predict_proba(x_test)[:,1]  
    report = answer > 0.5  
    print(classification_report(y_test, report, target_names = ['neg', 'pos']))
    print("--------------------")
    from sklearn.metrics import accuracy_score
    print('???: %.2f' % accuracy_score(y_test, doc_class_predicted))