This repository contains a code for plotting the decision boundary of a 2D binary classifier, implemented by a shallow neural network with arbitrary number of hidden neurons. The main code can be found in the notebook decisionBoundary.ipynb, while the model and the visualizer are impemented functions.py. The simulation produces a GIF animation, showing different levels of network expressivity with increasing network complexity. Dependencies: tensorflow 2.18.0 and keras 3.8.0.
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A visualization of the decision boundary of a binary classifier, implemented by a shallow neural network with arbitrary number of hidden neurons.
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simoneroncallo/classifier-decision-boundary
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A visualization of the decision boundary of a binary classifier, implemented by a shallow neural network with arbitrary number of hidden neurons.
