ValueError:`axis`必须小于维度数（1）

Question

我想在混淆矩阵中显示我训练过的模型，但如果我运行我的方法，我会在以下代码中得到一个错误ytrue = np.argmax(y_test, axis=1).tolist()：

raise ValueError(f"axis must be fewer than the number of dimensions ({ndim})") ValueError: axis must be fewer than the number of dimensions (1)

我的代码里写了什么

df = pd.read_csv("data.csv")
X = df.drop(['Rin'], axis=1)
y = df['Rin']
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=.2)


model = Sequential()
model.add
...

model.save('tfmodel.h5')

model.load_weights('tfmodel.h5')

yhat = model.predict(X_test)
ytrue = np.argmax(y_test, axis=1).tolist()
yhat = np.argmax(yhat, axis=1).tolist()

print(confusion_matrix(ytrue, yhat))