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jaungiers / Perceptron-Linear-Classifier

A simple single layer perceptron neural network classifier for linear classification

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Perceptron Linear Classifier

Overview

A simple single layer perceptron neural network with 3 input layers, 1 hidden layer and 1 output layer. The perceptron will classify linearly according a linear boundary line and converge to it using a training set of points.

Technical Info

  • The perceptron algorithm is contained in the Perceptron.py class file, with it's inputs being represented by the Inputs.py class.

  • The Run.py file contains the run code for a test case of a training/testing set (split 70/30%). It also assumes the linear boundary is given by the function f(x) which models a line of 2x+1.

Example Output

![Example Output 3 training 20 testing](https://raw.githubusercontent.com/jaungiers/Perceptron-Linear-Classifier/master/example output/perceptron_linear_classifier_1.png)

![Example Output 5 training 100 testing](https://raw.githubusercontent.com/jaungiers/Perceptron-Linear-Classifier/master/example output/perceptron_linear_classifier_2.png)

![Example Output 100 training 1000 testing](https://raw.githubusercontent.com/jaungiers/Perceptron-Linear-Classifier/master/example output/perceptron_linear_classifier_3.png)

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A simple single layer perceptron neural network classifier for linear classification

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