IEEE

Multi-Class Classification of BMI Categories with Logistic Regression, SVM, Random Forest, and XGBoost

Abstract: Body Mass Index is a main indicator for assessing weight related health risks and classifying individuals listed as underweight, normal, overweight or obese. Accurate prediction of BMI ...
IEEE

Fuzzy LASSO Logistic Regression: A Regularized Framework for Interpretable Binary Classification Under Uncertainty

Abstract: Fuzzy classification models are important for handling uncertainty and heterogeneity in high-dimensional data. Although recent fuzzy logistic regression approaches have demonstrated ...
Mashable

The Brick screen time blocker is an even better value when multiple people use it

All products featured here are independently selected by our editors and writers. If you buy something through links on our site, Mashable may earn an affiliate commission. However, there's one big ...
Hosted on MSN

Python neural network for multiclass classification using softmax

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...
Scientific Research Publishing

Heart Disease Prediction: A Logistic Regression Approach ()

1 School of Computing and Data Science, Wentworth Institute of Technology, Boston, USA. 2 Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA. 3 ...
The New York Times

South Korea Outlaws the Use of Smartphones During Class

It becomes the latest country to restrict phone use in schools, with a law that will go into effect in 2026. By Choe Sang-Hun Reporting from Seoul South Korea passed a bill on Wednesday outlawing the ...
GitHub

Multi-class Image Classification for Unbalanced Fashion Data

This project investigates the impact of class imbalance on multi-class classification using an MLP classifier trained on a modified subset of the FashionMNIST dataset. The goal was to evaluate ...
Frontiers

A comparative analysis of binary and multi-class classification machine learning algorithms to detect current frailty status using the English longitudinal study of ageing (ELSA)

Physical frailty is a pressing public health issue that significantly increases the risk of disability, hospitalization, and mortality. Early and accurate detection of frailty is essential for timely ...