When the Dallas Mavericks left for the longest road trip of their season in late January, the team’s franchise player wasn’t with them. Luka Dončić had suffered a calf strain in a game on Christmas ...

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: ...

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.

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 ...

This project explores the concepts and applications of decision trees in machine learning, with explanations and implementation entirely in Persian. It is a valuable resource for Persian-speaking data ...

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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 ...

Objective: To investigate the risk factors associated with cognitive frailty among older adults in nursing homes using logistic regression and decision tree modeling, and to compare the predictive ...

Objectives This study aims to determine whether machine learning can identify specific combinations of long-term conditions (LTC) associated with increased sarcopenia risk and hence address an ...

Abstract: This study investigates the application of Decision Tree analysis to optimize test item selection in the development of mathematical procedures, particularly in the domains of Measurement ...