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Consider the following code that we used to classify the income of adults in the US . inputs = tf . keras.layers.Dense ( units =

Consider the following code that we used to classify the income of adults in the US.
inputs = tf.keras.layers.Dense(units=32, activation='relu', input_shape=[len(features.columns)])
hidden = tf.keras.layers.Dense(units=32, activation='relu')
outputs = tf.keras.layers.Dense(units=2, activation=TO BE FILLED)
model = tf.keras.Sequential([inputs, hidden, outputs])
loss = 'sparse_categorical_crossentropy'
optimizer = tf.keras.optimizers.RMSprop(0.001)
model.compile(loss=loss, optimizer=optimizer, metrics=['accuracy'])
What was the activation function used on the output layer in this deep neural network?
Group of answer choices
softmax
relu
sigmoid
softplus
tanh

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