Overview: Algorithm selection is an engineering decision: the wrong choice can freeze a system at scale, regardless of ...

Data clustering and classification have become indispensable for extracting actionable insights from large-scale, heterogeneous datasets characterised by high volume, velocity and variety. Clustering ...

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 ...

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 ...

Abstract: Because of their transparency, interpretability, and efficiency in classification tasks, decision tree algorithms are the foundation of many Business Intelligence (BI) and Analytics ...

When it comes to choosing a tree for a landscape, homeowners consider many things. Some plant trees for their aesthetic appeal, while others do so for their fruit. However, there are also many people ...

Automatic decision tree generation from decision tables provided. This tool leverages machine learning algorithms to streamline the transformation of structured decision tables into interpretable and ...

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 ...

Arid and semiarid regions face challenges such as bushland encroachment and agricultural expansion, especially in Tiaty, Baringo, Kenya. These issues create mixed opportunities for pastoral and ...