Objectives Declining physical fitness, rising obesity and mental and behavioural diagnoses are growing public health issues in young adults. This study aimed to examine the associations between ...

Background Endovascular therapy (EVT) is standard treatment for large vessel occlusion in patients with a National Institutes ...

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

A complete implementation of Logistic Regression with Gradient Descent optimization from scratch using only NumPy, demonstrating mathematical foundations of binary classification for diabetes ...

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 goal of a machine learning binary classification problem is to predict a variable that has exactly two possible values. For example, you might want to predict the sex of a company employee (male = ...

Doing logistic regression with a binary outcome using the Generalized Linear Model analysis in Regression module should work. This works fine in Regression > Logistic Regression.

This cross-sectional study investigates the interplay of lifestyle, behavioral, and psychosocial factors in predicting depressive symptoms among Chinese college students (N=508) using binary logistic ...