Fork Author: Kevin Paniagua Romero
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.
Counterfactual explanations with genetic algorithms and estimation of distribution algorithms and a Bayesian ensemble
Important to change init.py inside the folder with the rute to R. Also you need to have installed R and bnclassify on it. #In this forked version I will be adapting this work into using Dash with a web interface in order to be implemented in a bigger web app called (BayesInterpret).