Logistic regression was developed starting in the late 1930s as an effort to improve a binary classification technique called probit regression. Even though several more recently developed techniques, ...

The is sometimes called multi-class logistic regression. But in my opinion, using an alternative classification technique, a neural network classifier, is a better option. Logistic regression can ...

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 ...

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.

Samples of diseased cases and nondiseased controls are drawn at random from the population at risk. After classification according to the exposure of interest, subsamples of cases and controls are ...

First off, you need to be clear what exactly you mean by advantages. People have argued the relative benefits of trees vs. logistic regression in the context of interpretability, robustness, etc.