APPLICATION OF SUPERVISED LEARNING
NEURAL NETWORK
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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How many output layers are required for constructing an Artificial Neural Network?
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1
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3
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2
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None of the above
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Explanation:
Detailed explanation-1: -There are three layers in the network architecture: the input layer, the hidden layer (more than one), and the output layer. Because of the numerous layers are sometimes referred to as the MLP (Multi-Layer Perceptron).
Detailed explanation-2: -Explanation: There must always be only one output layer.
Detailed explanation-3: -If data is less complex and is having fewer dimensions or features then neural networks with 1 to 2 hidden layers would work. If data is having large dimensions or features then to get an optimum solution, 3 to 5 hidden layers can be used.
Detailed explanation-4: -The neural network consists of three layers: an input layer, i; a hidden layer, j; and an output layer, k.
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