正确绘制混淆矩阵

Question

import matplotlib.pyplot as plt
from keras.models import load_model


plt.plot(history.history['accuracy'])
plt.plot(history.history['val_accuracy'])
plt.title('model accuracy')
plt.ylabel('accuracy')
plt.xlabel('epoch')
plt.legend(['train', 'test'], loc='upper left')
plt.show()
# summarize history for loss
plt.plot(history.history['loss'])
plt.plot(history.history['val_loss'])
plt.title('model loss')
plt.ylabel('loss')
plt.xlabel('epoch')
plt.legend(['train', 'test'], loc='upper left')
plt.show()

I am getting error while trying to plot confusion matrix for the below code snippet

from sklearn.metrics import confusion_matrix
pred = model.predict(X_test)
pred = np.argmax(pred,axis = 1) 
y_true = np.argmax(y_test,axis = 1)

The error for the above snippet say "NameError: name 'model' is not defined"

CM = confusion_matrix(y_true, pred)
from mlxtend.plotting import plot_confusion_matrix
fig, ax = plot_confusion_matrix(conf_mat=CM ,  figsize=(5, 5))
plt.show()

The error for the above snippet says "NameError: name 'y_true' is not defined"

error image

Answer 1

y_true is not defined because the previous cell (where the model error occurs) does not complete. As you define y_true in the same cell where the model not defined error occurs, the cell doesn't execute the rest of the lines, hence y_true is not defined.

The first error then, model not defined is happening because you haven't assigned anything to the variable model . This should be fixed first ie :

model = load_model(<filepath to your saved model>)