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.

The data doctor continues his exploration of Python-based machine learning techniques, explaining binary classification using logistic regression, which he likes for its simplicity.

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

Purpose To calculate and validate a linear discriminant function (LDF) for scanning laser polarimetry (SLP) with variable corneal compensation (GDx-VCC) to increase the diagnostic accuracy when ...

Binary-response regression models in which the link function is a family defined by one or more unknown shape parameters are considered. Detailed attention is given to the two single-parameter ...

The LOGISTIC and PROBIT procedures can perform logistic and ordinal logistic regression. See Chapter 5, "Introduction to Categorical Data Analysis Procedures," Chapter 39, "The LOGISTIC Procedure," ...

We accommodate the longitudinal nature of the multiple outcomes with a unique extension of the nested random effects logistic model with an autoregressive structure to include drop-out and baseline ...

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