If you’ve ever tried to build a agentic RAG system that actually works well, you know the pain. You feed it some documents, cross your fingers, and hope it doesn’t hallucinate when someone asks it a ...

College of Chemistry and Chemical Engineering, Liaoning Normal University, Dalian, Liaoning 116029, China ...

Abstract: This paper proposes a production decision analysis model based on decision tree and Bayesian optimisation, aiming to optimise the decision-making in the production process of enterprises.

Objective: To develop a decision tree model using clinical risk factors to predict massive pulmonary hemorrhage (MPH) and MPH-related mortality in extremely low birth weight infants (ELBWIs). Method: ...

Decision trees are a powerful tool for decision-making and predictive analysis. They help organizations process large amounts of data and break down complex problems into clear, logical steps. Used in ...

V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Sciences, Moscow 119334, Russia ...

Along the iconic Sunset Boulevard in Hollywood, palm trees line both sides of the roadway. They tower above the tourists and traffic, synonymous with Los Angeles in the minds of visitors. About 8 ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of decision tree regression using the C# language. Unlike most implementations, this one does not use recursion ...

Decision tree is an effective supervised learning method for solving classification and regression problems. This article combines the Pearson correlation coefficient with the CART decision tree, ...