Bayesian Algorithm Implementation in MATLAB

This document provides a comprehensive guide to installing and utilizing Bayesian algorithms in MATLAB. To install the Bayesian algorithm package, we first need to download FullBNT (Bayesian Network Toolkit) and add it to MATLAB's search path. This can be accomplished by executing the following commands in the terminal: cd /home/ai2/murphyk/matlab git clone https://github.com/BNT-ANU/FactorGraphs/archive/master.zip unzip master.zip cd FullBNT addpath(genpathKPM('/home/ai2/murphyk/matlab/FullBNT')) savepath The `addpath(genpathKPM(...))` command recursively adds all subdirectories of FullBNT to MATLAB's path, ensuring access to all Bayesian network functions and utilities. The `savepath` command persists these path changes across MATLAB sessions. Once installed, users can leverage MATLAB's Bayesian algorithms for probabilistic modeling, featuring key functions for Bayesian inference, network structure learning, and probabilistic reasoning. The toolbox enables sophisticated data analysis capabilities including probability distribution handling, conditional probability calculations, and graphical model implementations, providing researchers with powerful tools for statistical modeling and machine learning applications.