MATLAB Bayesian Network Toolbox - FullBNT-1.0.5 Release

You can download the latest version of the MATLAB Bayesian Network Toolbox FullBNT-1.0.5.zip from the following link: [Link]

FullBNT-1.0.5.zip is an open-source software toolbox based on Bayesian networks, designed to provide comprehensive methods for modeling, inference, and learning of various Bayesian network architectures. The toolbox implements key algorithms including exact inference methods like the junction tree algorithm and approximate techniques such as likelihood weighting. It contains multiple practical algorithms and tools that can help solve diverse problems including classification using naive Bayes models, clustering with mixture models, and regression analysis through conditional probability distributions. The package includes core functions for structure learning (e.g., K2 algorithm), parameter estimation (EM algorithm), and probabilistic inference operations. Additionally, it provides extensive documentation and tutorials with code examples demonstrating how to create Bayesian networks using the toolbox's object-oriented interface, perform evidence propagation, and conduct parameter learning from data.

Please note that FullBNT-1.0.5.zip is an open-source toolbox released under favorable licensing terms, allowing free use, modification, and distribution. The source code is organized in modular structure with separate directories for graph operations, inference engines, and learning modules. If you encounter any issues during implementation or have questions about specific functions like the Bayes net structure learning algorithms, please feel free to contact us. Thank you for using our toolbox!