MLP refers to Multi Layer Perceptron. It refers to a fully connected part of feedforward artificial neutral network. Sometimes it refers to networks which comprise multiple layers of perceptrons.
Multilayer Perceptron works by generating a set of outputs from the given inputs. It has several layers of input nodes that establish a direct connection between the input and the output layers. To train a network, it uses backpropagation.
In case of summation, all features and their weights are first multiplied and later summed up. This summed up function is then applied over an Activation function. We then multiply the output form the neuron with the weight and supply it as input to the output layer.
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