Stian Lydersen, PhD, professor of medical statistics at the Regional Centre for Child and Youth Mental Health and Child Welfare, Department of Mental Health, Norwegian University of Science and ...

Abstract: Fire occurrence probability mapping provides a detailed understanding of the spatial distribution of the fire occurrence probability and it is useful in fire management. The binary logistic ...

Researchers developed a data-driven framework for autonomous tomato harvesting, improving success rates through YOLOv8-based ...

Objectives Functional foods have demonstrated potential in preventing gastrointestinal and musculoskeletal (osteo-related) ...

In a randomized clinical trial, researchers compared the effect of single vs multiple treatment alternatives on care decisions.

This page works through an example of fitting a logistic model with the iteratively-reweighted least squares (IRLS) algorithm. If you'd like to examine the algorithm in more detail, here is Matlab ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

ABSTRACT: Road traffic accidents are one of the global safety and socioeconomic challenges. According to WHO (2024), it has caused over 1.19 million annual fatalities. It is also projected to cause ...

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...