I'm using two different functions to calculate the accuracy of my deep learning model and I am confused which one is which.
The first one is
loss, accuracy = model.evaluate(x_train, y_train, verbose=0) print('Accuracy: %f' % (accuracy)) print('Loss: %f' % (loss)) Accuracy: 0.731495 Loss: 1.136258
And the second way is to obtain the accuracy:
test_accuracy = history2.history['val_acc']
Accuracy is 0.731 and test_accuracy is around 0.21 Which is one is my models' accuracy