之前的DNN分类问题，解决了上面一个bug,后面又出现了一个问题：
import scipy.sparse
xtest_count=scipy.sparse.lil_matrix(xtest_count).toarray()
ytest_count = scipy.sparse.lil_matrix(ytest_count).toarray()
predictions = model.predict(xtest_count, batch_size=512)
predictions = np.argmax(predictions)
from sklearn.metrics import classification_report, confusion_matrix, accuracy_score
import pandas as pd
cm = confusion_matrix(ytest_count, predictions)
cm_df = pd.DataFrame(cm.T, index=encoder.classes_, columns=encoder.classes_)
cm_df.index.name = 'Predicted'
cm_df.columns.name = 'True'
print(cm_df)
--------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-24-7ec755bc0a87> in <module>()
1 from sklearn.metrics import classification_report, confusion_matrix, accuracy_score
2 import pandas as pd
----> 3 cm = confusion_matrix(ytest_count, predictions)
4 cm_df = pd.DataFrame(cm.T, index=encoder.classes_, columns=encoder.classes_)
5 cm_df.index.name = 'Predicted'
4 frames
/usr/local/lib/python3.7/dist-packages/sklearn/utils/validation.py in _num_samples(x)
268 if len(x.shape) == 0:
269 raise TypeError(
--> 270 "Singleton array %r cannot be considered a valid collection." % x
271 )
272 # Check that shape is returning an integer or default to len
TypeError: Singleton array 14 cannot be considered a valid collection.
请大家帮忙解答，谢谢。
混淆矩阵必须输入列表形式的，检查下你的数据
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