A new research paper shows the approach performs significantly better than the random-walk forecasting method.

Background: Stress-induced hyperglycemia (SHG) represents a significant metabolic complication in non-diabetic cardiac surgery older adult patients, with substantial implications for postoperative ...

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 ...

Student dropout in primary education is a critical global challenge with significant long-term societal and individual consequences. Early identification of at-risk students is a crucial first step ...

Introduction: Stroke remains one of the leading causes of global mortality and long-term disability, driving the urgent need for accurate and early risk prediction tools. Traditional models such as ...

This repository contains the complete implementation of a BSc Statistics dissertation investigating supervised learning approaches for fraud risk scoring in Nigerian financial transactions. The ...

Abstract: To compare the accuracy of the Random Forest algorithm with the Novel Logistic Regression Technique in order to predict the data quality issues for the voice emotion identification system.

This project focuses on building a machine learning model to predict the approval status of loan applications based on applicant information. It explores data preprocessing, visualization, feature ...

Abstract: This paper aims to predict the diagnosis of Autism Spectrum Disorder (ASD) using the application of a few machine learning algorithms for comparison purposes to determine the performance of ...