ABSTRACT: The objective of this work is to determine the true owner of a land—public or private—in the region of Kumasi (Ghana). For this purpose, we applied different machine learning methods to the ...

Machine learning algorithms are often categorized as lazy learners or eager learners based on how they learn and make predictions. Among these, the K-Nearest Neighbor (KNN) algorithm stands out as a ...

Sequentia is a Python package that provides various classification and regression algorithms for sequential data, including methods based on hidden Markov models and dynamic time warping. Some ...

As we progress into 2025, Artificial Intelligence (AI) continues to reshape industries and revolutionize how we interact with technology. For those starting their journey in AI, it’s essential to ...

Malnutrition among children in third-world countries like the Philippines remains a critical issue addressed by the UN’s Zero Hunger goal. Traditional methods such as K-Nearest Neighbor face ...

In the rapidly evolving landscape of business analytics, machine learning algorithms have become indispensable tools for extracting insights, making predictions, and automating decision-making ...

K-Nearest Neighbors (KNN) is a simple yet effective supervised machine learning algorithm used for both regression and classification tasks. The algorithm works by finding the K nearest data points in ...

Alzheimer’s disease (AD) is a widely frequent form of neurodegenerative brain disease 1. It is responsible for the psychological decline of up to three-quarters of all patients with dementia, which is ...

Disease risk prediction is a rising challenge in the medical domain. Researchers have widely used machine learning algorithms to solve this challenge. The k-nearest neighbour (KNN) algorithm is the ...

Endoscopic imaging plays a very important role in the diagnosis and treatment of lesions. However, the imaging range of endoscopes is small, which may affect the doctors' judgment on the scope and ...