IEEE

Research on the Enhancement and Improvement of Logistic Regression Models

Abstract: The logistic regression model is a linear model widely used for two-category classification problems. This report examines the enhancement and improvement methods of logistic regression ...
IEEE

Implementation of Logistic Regression for Classification of Chronic Kidney Disease with and without Comorbidities: A Performance Evaluation

Abstract: Chronic kidney disease (CKD) is a highly progressive condition that can lead to kidney failure and requires early detection to prevent serious complications. This study analyzes the ...
C&EN

Predicting the Properties of IL-Solvent Electrolytes Using a Hybrid Support Vector Classification and Gradient Boosting Regression (SVC-GBR) Framework

Henry Krumb School of Mines, Earth and Environmental Engineering Department, Columbia University, New York, New York 10027, United States ...
Frontiers

Evaluating machine learning models for stroke prediction based on clinical variables

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 ...
SciELO

Obesity classification: a comparative study of machine learning models excluding weight and height data

OBJECTIVE: Obesity is a global health problem. The aim is to analyze the effectiveness of machine learning models in predicting obesity classes and to determine which model performs best in obesity ...