Explainable Machine Learning for Predicting Land Surface Temperature Dynamics in Southern Kaduna, Nigeria: A Random Forest and SHAP-Based Approach

Explainable Machine Learning for Detecting Fraudulent Online Job Postings in Ghana: A SHAP-Based Approach

Abstract Employment fraud through online job postings is an increasing concern in

SHAP-Based Explainable Machine Learning for Predicting Loan Default among Women-Owned Microenterprises in Kenya

Background: Access to credit remains a major challenge for women-owned microenterprises in sub-Sahar

Predicting terrestrial heat flow in Egypt using random forest regression: a machine learning approach

Abstract This work aims to create a machine-learning model that can contribute to a comprehensive un

Explainable Detection of Obfuscated Malicious PowerShell Scripts Using CodeBERT, Random Forest, and Multi-Method SHAP Explainable Detection of Obfuscated Malicious PowerShell Scripts Using CodeBERT, Random Forest, and Multi-Method SHAP

This dataset contains the complete supplementary materials for the paper "Explainable Detection of O

GEO-SPATIAL APPROACH FOR FOREST COVER DYNAMICS AND ITS RELATIONSHIP WITH LAND SURFACE TEMPERATURE AND RAINFALL IN AWI ZONE, ETHIOPIA

Machine Learning-Based Modeling of Land Surface Temperature in Lagos, Nigeria: Integrating Canopy Structure, Built Environment, and Surface Reflectance Variables

Abstract Urban heat is an escalating environmental challenge in tropical megacitie