Logistic regression is a powerful technique for fitting models to data with a binary response variable, but the models are difficult to interpret if collinearity, nonlinearity, or interactions are ...

Journal of the Royal Statistical Society. Series D (The Statistician) A three-parameter family of survival models is introduced. The base-line density is derived and the main properties of the model, ...

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 ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end program that explains how to perform binary classification (predicting a variable with two possible discrete values) using ...

Li, Y. and Liu, J. (2025) An Accessible Predictive Model for Alzheimer’s Disease Based on Cognitive and Neuropathological ...

Multicenter Phase I/II Study of Cetuximab With Paclitaxel and Carboplatin in Untreated Patients With Stage IV Non–Small-Cell Lung Cancer Data from 1,066 patients recruited from nine European centers ...

Cursor stated in its blog that achieving a high acceptance rate involves not only making the model smarter but also understanding when to provide suggestions and when not to. To tackle this challenge, ...