APPLICATION OF SUPERVISED LEARNING
NEURAL NETWORK
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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multilayer perceptron
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single layer perceptron
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two layer perceptron
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None of the above
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Detailed explanation-1: -Perceptron is a neural network with only one neuron, and can only understand linear relationships between the input and output data provided. However, with Multilayer Perceptron, horizons are expanded and now this neural network can have many layers of neurons, and ready to learn more complex patterns.
Detailed explanation-2: -It consists of two layers of neurons. The first layer is known as hidden layer, and the second layer, known as the output layer, consists of a single neuron.
Detailed explanation-3: -Multilayered Networks have at least one hidden layer (all the layers between the input and output layers are hidden). A single-layer perceptron can only learn linear functions, but Multilayered Perceptrons can also learn non-linear functions.