Personalized algorithms may quietly sabotage how people learn, nudging them into narrow tunnels of information even when they start with zero prior knowledge. In the study, participants using ...

Accurate land use/land cover (LULC) classification remains a persistent challenge in rapidly urbanising regions especially, in the Global South, where cloud cover, seasonal variability, and limited ...

A decision tree regression system incorporates a set of if-then rules to predict a single numeric value. Decision tree regression is rarely used by itself because it overfits the training data, and so ...

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 ...

1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...

The original version of this story appeared in Quanta Magazine. If you want to solve a tricky problem, it often helps to get organized. You might, for example, break the problem into pieces and tackle ...

Abstract: The decision tree, as an efficient data structure, is commonly used to perform packet classification due to its faster classification speed. During packet classification, all packets need to ...

Green vegetation is an essential part of natural resources and is vital to the ecosystem. Simultaneously, with improving people’s living standards, food security and the supply of forage resources ...

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 ...