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 ...
IEEE

Predictive Analysis of Network-Based Attacks by Hybrid Machine Learning Algorithms Utilizing Bayesian Optimization, Logistic Regression, and Random Forest Algorithm

Abstract: These days, intrusion detection systems are one of the newest trends in society. These technologies serve as a defense against a variety of security breaches, the number of which has been ...
Frontiers

A clinical prediction model for delirium tremens: development and validation in alcohol-dependent patients using multivariable logistic regression

Delirium tremens (DT) is a severe complication of alcohol withdrawal. This study aimed to develop and validate a prediction model for DT risk in hospitalized patients with alcohol dependence, using ...