This article will cover the basic theory behind logistic regression, the types of logistic regression, when to use them and take you through a worked example.

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 ...

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.

Regression can be used on categorical responses to estimate probabilities and to classify.

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

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 ...

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 ...

What are the advantages of logistic regression over decision trees? This question was originally answered on Quora by Claudia Perlich.