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

Error Function Regularization: A New Approach to Sparse Logistic Regression

Abstract: We introduce the ERror Function (ERF) for sparse logistic regression. The ERF regularization interpolates between the $\mathrm{L}_{0}$ norm, which measures the number of non-zero elements in ...
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 ...
GitHub

abdullah-v-cmd/ML-PipeLine-End-to-End

ML Pipeline is a comprehensive, full-stack machine learning platform built on Cloudflare Pages that enables users to manage the complete lifecycle of machine learning projects through an intuitive web ...