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 ...

"Logistic and Poisson Regression," Wednesday, November 5: The fourth LISA mini course focuses on appropriate model building for categorical response data, specifically binary and count data. The most ...

I predict you'll find this logistic regression example with R to be helpful for gleaning useful information from common binary classification problems. Logistic regression is a technique used to make ...

Dr. James McCaffrey of Microsoft Research demonstrates applying the L-BFGS optimization algorithm to the ML logistic regression technique for binary classification -- predicting one of two possible ...

Linear mixed models are increasingly used for the analysis of genome-wide association studies (GWAS) of binary phenotypes because they can efficiently and robustly account for population ...

This short course provides an introduction to regression analysis, a commonly used method to study the relationship between a response variable and one or more explanatory variables. The course will ...

As the coronavirus disease 2019 (COVID-19) pandemic has spread across the world, vast amounts of bioinformatics data have been created and analyzed, and logistic regression models have been key to ...

The following table details the results of a series of statistical models predicting various measures related to people’s attitudes toward electric vehicles from a set of explanatory variables, or ...