Python Ipynb：分类指标可以'；t处理二进制和多标签指示器目标的混合，ValueError

链接到colab笔记本- 我无法解决下面提到的错误。请帮忙

1030/1030 [==============================] - 3s 3ms/step - loss: 0.1726 - accuracy: 0.9262

accuracy: 92.62%
The AUC FOR transformer approach IS 0.0879245139775392

[[ True False]
 [False  True]
 [ True False]
 ...
 [False  True]
 [ True False]
 [ True False]]
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-20-b62407ca5b02> in <module>()
     27 print(y_pred)
     28 from sklearn.metrics import confusion_matrix,accuracy_score
---> 29 cm = confusion_matrix(yts, y_pred)
     30 accuracy=accuracy_score(yts,y_pred)
     31 print("Confusion matrix for   transformer approach is",cm)

1 frames
/usr/local/lib/python3.6/dist-packages/sklearn/metrics/_classification.py in _check_targets(y_true, y_pred)
     88     if len(y_type) > 1:
     89         raise ValueError("Classification metrics can't handle a mix of {0} "
---> 90                          "and {1} targets".format(type_true, type_pred))
     91 
     92     # We can't have more than one value on y_type => The set is no more needed

ValueError: Classification metrics can't handle a mix of binary and multilabel-indicator targets

1030/1030[=====================================]-3s 3ms/步-损耗：0.1726-精度：0.9262
准确率：92.62%
变压器进近的AUC为0.0879245139775392
[[真假]
[假-真]
[真假]
...
[假-真]
[真假]
[对错]]
---------------------------------------------------------------------------
ValueError回溯（最近一次调用上次）
在（）
27打印（y_pred）
28从sklearn.metrics导入混淆矩阵、准确性得分
--->29厘米=混乱矩阵（yts，y_pred）
30准确度=准确度得分（yts，y\U pred）
31打印（“变压器方法的混淆矩阵为”，cm）
1帧
/usr/local/lib/python3.6/dist-packages/sklearn/metrics//u classification.py in\u check\u目标（y\u true，y\u pred）
88如果透镜（y_型）>1：
89 raise VALUERROR（“分类度量无法处理{0}的混合”
--->90“和{1}个目标”。格式（type_true，type_pred））
91
92#在y_type=>上不能有多个值，该集合不再需要
ValueError：分类指标无法处理二进制和多标签指标目标的混合