Python 从 Keras 多类模型中获取混淆矩阵
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Get Confusion Matrix From a Keras Multiclass Model
提问by ATMA
I am building a multiclass model with Keras.
我正在用 Keras 构建一个多类模型。
model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])
model.fit(X_train, y_train, batch_size=batch_size, epochs=epochs, verbose=1, callbacks=[checkpoint], validation_data=(X_test, y_test)) # starts training
Here is how my test data looks like (it's text data).
这是我的测试数据的样子（它是文本数据）。
X_test
Out[25]:
array([[621, 139, 549, ..., 0, 0, 0],
[621, 139, 543, ..., 0, 0, 0]])
y_test
Out[26]:
array([[0, 0, 1],
[0, 1, 0]])
After generating predictions...
生成预测后...
predictions = model.predict(X_test)
predictions
Out[27]:
array([[ 0.29071924, 0.2483743 , 0.46090645],
[ 0.29566404, 0.45295066, 0.25138539]], dtype=float32)
I did the following to get the confusion matrix.
我做了以下工作来获得混淆矩阵。
y_pred = (predictions > 0.5)
confusion_matrix(y_test, y_pred)
Traceback (most recent call last):
File "<ipython-input-38-430e012b2078>", line 1, in <module>
confusion_matrix(y_test, y_pred)
File "/Users/abrahammathew/anaconda3/lib/python3.6/site-packages/sklearn/metrics/classification.py", line 252, in confusion_matrix
raise ValueError("%s is not supported" % y_type)
ValueError: multilabel-indicator is not supported
However, I am getting the above error.
但是，我收到上述错误。
How can I get a confusion matrix when doing a multiclass neural network in Keras?
在 Keras 中进行多类神经网络时如何获得混淆矩阵？
回答by Neabfi
Your input to confusion_matrixmust be an array of int not one hot encodings.
您的输入confusion_matrix必须是一个 int 数组，而不是一个热编码。
matrix = metrics.confusion_matrix(y_test.argmax(axis=1), y_pred.argmax(axis=1))
