Multilayer Perceptron

Download Example XORMultilayerPerceptron C# project

Multilayer Perceptron - Creation

Multilayer perceptron is a feed forward neural network that is trained through supervised learning and is used in classification of inputs into appropriate outputs. Multilayer perceptron is best thought of as a network of perceptrons separated into layers with each perceptron connected to all perceptrons in both neighboring layers. Perceptrons in the network, with the exception of input layer, use nonlinear activation function so that the multilayer perceptron can be used to solve problems where data is not linearly separable – for example XOR problem in provided sample code.

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Multiclass Perceptron in C#

Download Multiclass Perceptron C# Project

In order to understand multiclass perceptron prior knowledge of binary perceptron is required.

Multiclass Perceptron is used for classifying input data into linearly separable classes. Each class in a multiclass perceptron has a separate set of input weights. Just like in a simple perceptron the inputs are multiplied by weights and then summed, but instead of score passing through an activation function the class with the highest score is chosen.


Multiclass Perceptron

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