title: how to print confusion matrix of keras Multi output?
body: <p>I have one question.
  I want to print a confusion matrix.
  my model is functional api of keras.
  and 
  model = Model(inputs=[data_input], outputs=[output_1, output_2])</p>
  
  <p>output_1 = 9 classes
  output_2 = 5 classes</p>
  
  <p><strong>My multi-classification model</strong></p>
  
  <pre><code>data_input = Input(shape=(trainX.shape[1], trainX.shape[2]))
  
  Conv1 = Conv1D(filters=50, kernel_size=4, padding='valid',  activation='relu', strides=1)(data_input)
  Conv1 = MaxPooling1D(pool_size=2)(Conv1)
  
  Conv2 = Conv1D(filters=50, kernel_size=4, padding='valid', activation='relu', strides=1)(Conv1)
  Conv2 = MaxPooling1D(pool_size=2)(Conv2)
  
  Conv3 = Conv1D(filters=50, kernel_size=4, padding='valid', activation='relu', strides=1)(Conv2)
  Conv3 = MaxPooling1D(pool_size=2)(Conv3)
  
  Classification1 = LSTM(128, input_shape=(47, 50), return_sequences=False)(Conv3)
  Classification2 = GRU(128, input_shape=(47, 50), return_sequences=False)(Conv3)
  
  activity = Dense(9)(Classification1)
  activity = Activation('softmax')(activity)
  
  speed = Dense(5)(Classification2)
  speed = Activation('softmax')(speed)
  
  model = Model(inputs=[data_input], outputs=[activity, speed])
  
  model.compile(loss= 'categorical_crossentropy' , optimizer='adam', metrics=[ 'accuracy' ])
  print(model.summary())
  
  history = model.fit(trainX, {'activation_1': trainY_Activity, 'activation_2': trainY_Speed},
            validation_data=(testX, {'activation_1': testY_Activity, 'activation_2': testY_Speed}),
            epochs=epochs, batch_size=batch_size, verbose=1, shuffle=False)
  </code></pre>