In today’s data-driven world, simplicity often wins. One such tool that offers both power and interpretability is the Decision Tree, a fundamental machine learning algorithm that continues to play a ...

This is a Python implementation of my previous project Business Rules Reasoning System, enhanced with a reasoning orchestrator that leverages Large Language Models (LLMs) to enable a fully transparent ...

Les E. Atlas, Ronald A. Cole, Jerome T. Connor, Mohamed A. El-Sharkawi, Robert J. Marks II, Yeshwant K. Muthusamy, Etienne Barnard [Paper] ...

Random Forests (RFs) are among the most successful machine-learning algorithms in terms of prediction accuracy. In many domain problems, however, the primary goal is not prediction, but to understand ...

Classification approaches that allow to extract logical rules such as decision trees are often considered to be more interpretable than neural networks. Also, logical rules are comparatively easy to ...

Bayesian Decision Trees provide a probabilistic framework that reduces the instability of Decision Trees while maintaining their explainability. While Markov Chain Monte Carlo methods are typically ...

With the development of data mining, machine learning offers opportunities to improve discrimination by analyzing complex interactions among massive variables. To test the ability of machine learning ...