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Fork Author: Kevin Paniagua Romero

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BayesInterpret is a computational project focused on creating interactive dashboards for interpreting and visualizing machine learning models using Dash. This fork is part of the BayesInterpret initiative, where the main goal is to apply an intuitive interface to existing implementations, making model outputs and analyses easier to understand and use.

This work is based on ideas and research from the Computational Intelligence Group (CIG) and integrates interface design with machine learning tools to enhance interpretability in a simple and practical way. I'll be using Dash for the new interface.

CIG UPM

ISL_BN

Interactive Structural Learning for discrete Bayesian network classifiers

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Dash implementation of Interactive Structural Learning for discrete Bayesian network classifiers

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  • Python 89.4%
  • CSS 10.6%