Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...

Abstract: This research paper presents a comprehensive study on the prediction of energy consumption for household appliances using machine learning algorithms, with a focus on regression models. The ...

Quadratic regression extends linear regression by adding squared terms and pairwise interaction terms, enabling the model to capture non-linear structure and predictor interactions. The article ...

Add a description, image, and links to the extreme-learning-machine topic page so that developers can more easily learn about it.

The rapid uptake of supervised machine learning (ML) in clinical prediction modelling, particularly for binary outcomes based on tabular data, has sparked debate about its comparative advantage over ...

ABSTRACT: This study presents the Dynamic Multi-Objective Uncapacitated Facility Location Problem (DMUFLP) model, a novel and forward-thinking approach designed to enhance facility location decisions ...

Predicting performance for large-scale industrial systems—like Google’s Borg compute clusters—has traditionally required extensive domain-specific feature engineering and tabular data representations, ...

Abstract: In this paper, a regression based machine learning model (Lasso) is used for the design of cavity backed slotted antenna. This type of antenna is commonly used in military and aviation ...

web-based house price prediction app using Flask and machine learning. Trained on the Boston Housing dataset with error handling and UI enhancements.

Summer learning loss, also known as the “summer slide,” represents a significant challenge in education where students experience academic regression during extended breaks from formal instruction.