There is indeed a vast literature on the design and analysis of decision tree algorithms that aim at optimizing these parameters. This paper contributes to this important line of research: we propose ...

Cui, J.X., Liu, K.H. and Liang, X.J. (2026) A Brief Discussion on the Theory and Application of Artificial Intelligence in ...

The ruling allowed immigration agents to stop people for reasons that lower courts had deemed likely unconstitutional. By Charlie Savage Reporting from Washington The Supreme Court on Monday ...

Computer vision systems combined with machine learning techniques have demonstrated success as alternatives to empirical methods for classification and selection. This study aimed to classify tomatoes ...

The ML Algorithm Selector is an interactive desktop application built with Python and Tkinter. It guides users through a decision-making process to identify suitable machine learning algorithms for ...

Abstract: This paper presents an automatic machine learning (autoML) algorithm to select a decision tree algorithm which is most suitable for the stated requirements by the user for classification.

Abstract: Decision tree algorithms are very useful approaches in data mining. Indeed, the C4.5 algorithm is a popular data classifier for machine learning. Nowadays there is a wide range of Big Data ...

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, ...