However, coding multi-class logistic regression from scratch has least four advantages over using a library. Your code can be small and efficient, you can avoid licensing and copyright issues, you ...

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 ...

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

The GLM procedure fits general linear models to data, and it can perform regression, analysis of variance, analysis of covariance, and many other analyses. The following features for regression ...

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.

Logistic regression with binary and multinomial outcomes is commonly used, and researchers have long searched for an interpretable measure of the strength of a particular logistic model. This article ...

A three-parameter family of survival models is introduced. The base-line density is derived and the main properties of the model, including a frailty interpretation, are discussed. Several different ...