Department of Mathematics, Statistics and Actuarial Science, Faculty of Health, Natural Resources and Applied Sciences, Namibia University of Science and Technology, Windhoek, Namibia. Food insecurity ...

The dataset used was a widely known credit card fraud detection benchmark obtained from Kaggle. It is notoriously imbalanced, ...

Study objective: In social epidemiology, it is easy to compute and interpret measures of variation in multilevel linear regression, but technical difficulties exist in the case of logistic regression.

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 ...

Linear and logistic regression models are essential tools for quantifying the relationship between outcomes and exposures. Understanding the mathematics behind these models and being able to apply ...

The Data Science Lab. Logistic Regression with Batch SGD Training and Weight Decay Using C#. Dr. James McCaffrey from Microsoft Research presents a complete end-to-end program that explains how to ...

Nonlinear regression is a form of regression analysis in which data fit to a model is expressed as a mathematical function.

This study used a Bayesian multilevel ordinal logistic regression to model, identify and analyse the factors linked to child malnutrition in Ghana. Setting The setting of the study was the household ...