Background Remission and low-disease activity are recommended targets in systemic lupus erythematosus (SLE), yet many ...

The lack of precise, autonomous tools for monitoring and classifying cattle behavior limits farmers’ ability to make proactive and informed decisions regarding grazing and herd management. Currently, ...

Abstract: Multi-class classification presents a significant challenge in supervised machine learning, and it is frequently applied across various real-world domains. Random Forest (RF) stands out as a ...

Predict and prevent customer churn in the telecom industry with our advanced analytics and Machine Learning project. Uncover key factors driving churn and gain valuable insights into customer behavior ...

Abstract: An innovative system designed to enhance communication for individuals using sign language. Developed in Python, the system leverages a Random Forest classifier to accurately interpret hand ...

ABSTRACT: 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 ...

ABSTRACT: In this study, multi-source remote sensing data and machine learning algorithms were used to delineate the prospect area of remote sensing geological prospecting in eastern Botswana. Landsat ...

The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.