Logistic regression is a statistical method used to examine the relationship between a binary outcome variable and one or more explanatory variables. It is a special case of a regression model that ...

There are dozens of code libraries and tools that can create a logistic regression prediction model, including Keras, scikit-learn, Weka and PyTorch. When training a logistic regression model, there ...

A new study investigated how logistic regression model training affects performance, and which features are best to include when examining datasets from individuals suffering from COVID-19.

This article presents a score test to check the fit of a logistic regression model with two or more outcome categories. The null hypothesis that the model fits well is tested against the alternative ...

Peiming Wang, Martin L. Puterman, Mixed Logistic Regression Models, Journal of Agricultural, Biological, and Environmental Statistics, Vol. 3, No. 2 (Jun., 1998), pp ...

Purpose To collect data for the development of a more universally useful logistic regression model to distinguish between a malignant and benign adnexal tumor before surgery. Patients and Methods ...