Keras - Plot training, validation and test set accuracy : <p>I want to plot the output of this simple neural network: </p>

<pre><code>model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
history = model.fit(x_test, y_test, nb_epoch=10, validation_split=0.2, shuffle=True)

model.test_on_batch(x_test, y_test)
model.metrics_names
</code></pre>

<p>I have plotted <em>accuracy</em> and <em>loss</em> of training and validation:</p>

<pre><code>print(history.history.keys())
#  "Accuracy"
plt.plot(history.history['acc'])
plt.plot(history.history['val_acc'])
plt.title('model accuracy')
plt.ylabel('accuracy')
plt.xlabel('epoch')
plt.legend(['train', 'validation'], loc='upper left')
plt.show()
# "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', 'validation'], loc='upper left')
plt.show()
</code></pre>

<p>Now I want to add and plot test set's accuracy from <code>model.test_on_batch(x_test, y_test)</code>, but from <code>model.metrics_names</code> I obtain the same value <em>'acc'</em> utilized for plotting accuracy on training data <code>plt.plot(history.history['acc'])</code>. How could I plot test set's accuracy?</p>
