X_train,X_test,y_train,y_test = train_test_split(x,y,test_size=0.3,random_state = 2020,stratify=y)   

X_train_user = X_train[y_train == 'ji2hwh']
X_train_attacker = X_train[y_train != 'ji2hwh']

outlier_prop = len(X_train_user) / len(X_train_attacker)

svm = OneclassSVM(kernel='rbf',nu=outlier_prop,gamma=0.000001) 
svm.fit(X_train_user)

pred = svm.predict(X_test)

y_test[y_test == 'ji2hwh'] = 1

y_test[y_test != 1] = -1

print(accuracy_score(y_test,pred))

我发现分类指标无法处理上述代码中混合的未知目标和二进制目标错误。 'ji2hwh' 只是一个用户 ID，我将其视为我的一类分类的目标用户，而将其余用户视为攻击者。 x 是一个特征向量，y 包含用户的 ID。我不知道为什么我会收到这个错误，因为变量 pred 返回一个带有 [-1,1] 值的 ndarray 并且 y_test 似乎正确分配了适当的值，也在同一组值 [-1,1] 中。我该怎么做才能克服这个编译错误？

整个错误信息：

  File "C:\Users\User\Desktop\MobileUserauth\data_exploration.py",line 94,in <module>
    print(accuracy_score(y_test,pred))

  File "C:\Users\User\anaconda3\lib\site-packages\sklearn\utils\validation.py",line 72,in inner_f
    return f(**kwargs)

  File "C:\Users\User\anaconda3\lib\site-packages\sklearn\metrics\_classification.py",line 187,in accuracy_score
    y_type,y_true,y_pred = _check_targets(y_true,y_pred)

  File "C:\Users\User\anaconda3\lib\site-packages\sklearn\metrics\_classification.py",line 90,in _check_targets
    raise ValueError("Classification metrics can't handle a mix of {0} "

ValueError: Classification metrics can't handle a mix of unknown and binary targets