Test score vs test accuracy when evaluating model using Keras : <p>Im using a neural network implemented with the Keras library and below is the results during training. At the end it prints a test score and a test accuracy. I can't figure out exactly what the score represents, but the accuracy I assume to be the number of predictions that was correct when running the test.</p>

<blockquote>
  <p>Epoch 1/15 1200/1200 [==============================] - 4s - loss:
  0.6815 - acc: 0.5550 - val_loss: 0.6120 - val_acc: 0.7525</p>
  
  <p>Epoch 2/15 1200/1200 [==============================] - 3s - loss:
  0.5481 - acc: 0.7250 - val_loss: 0.4645 - val_acc: 0.8025</p>
  
  <p>Epoch 3/15 1200/1200 [==============================] - 3s - loss:
  0.5078 - acc: 0.7558 - val_loss: 0.4354 - val_acc: 0.7975</p>
  
  <p>Epoch 4/15 1200/1200 [==============================] - 3s - loss:
  0.4603 - acc: 0.7875 - val_loss: 0.3978 - val_acc: 0.8350</p>
  
  <p>Epoch 5/15 1200/1200 [==============================] - 3s - loss:
  0.4367 - acc: 0.7992 - val_loss: 0.3809 - val_acc: 0.8300</p>
  
  <p>Epoch 6/15 1200/1200 [==============================] - 3s - loss:
  0.4276 - acc: 0.8017 - val_loss: 0.3884 - val_acc: 0.8350</p>
  
  <p>Epoch 7/15 1200/1200 [==============================] - 3s - loss:
  0.3975 - acc: 0.8167 - val_loss: 0.3666 - val_acc: 0.8400</p>
  
  <p>Epoch 8/15 1200/1200 [==============================] - 3s - loss:
  0.3916 - acc: 0.8183 - val_loss: 0.3753 - val_acc: 0.8450</p>
  
  <p>Epoch 9/15 1200/1200 [==============================] - 3s - loss:
  0.3814 - acc: 0.8233 - val_loss: 0.3505 - val_acc: 0.8475</p>
  
  <p>Epoch 10/15 1200/1200 [==============================] - 3s - loss:
  0.3842 - acc: 0.8342 - val_loss: 0.3672 - val_acc: 0.8450</p>
  
  <p>Epoch 11/15 1200/1200 [==============================] - 3s - loss:
  0.3674 - acc: 0.8375 - val_loss: 0.3383 - val_acc: 0.8525</p>
  
  <p>Epoch 12/15 1200/1200 [==============================] - 3s - loss:
  0.3624 - acc: 0.8367 - val_loss: 0.3423 - val_acc: 0.8650</p>
  
  <p>Epoch 13/15 1200/1200 [==============================] - 3s - loss:
  0.3497 - acc: 0.8475 - val_loss: 0.3069 - val_acc: 0.8825</p>
  
  <p>Epoch 14/15 1200/1200 [==============================] - 3s - loss:
  0.3406 - acc: 0.8500 - val_loss: 0.2993 - val_acc: 0.8775</p>
  
  <p>Epoch 15/15 1200/1200 [==============================] - 3s - loss:
  0.3252 - acc: 0.8600 - val_loss: 0.2960 - val_acc: 0.8775</p>
  
  <p>400/400 [==============================] - 0s</p>
  
  <p>Test score: 0.299598811865</p>
  
  <p>Test accuracy: 0.88</p>
</blockquote>

<p>Looking at the <a href="https://keras.io/models/model/" rel="noreferrer">Keras documentation</a>, I still don't understand what score is. For the evaluate function, it says: </p>

<blockquote>
  <p>Returns the loss value &amp; metrics values for the model in test mode.</p>
</blockquote>

<p>One thing I noticed is that when the test accuracy is lower, the score is higher, and when accuracy is higher, the score is lower.</p>
