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 ...

We will then proceed to Bayesian approaches to generalized linear models, including binary logistic regression, ordinal logistic regression, Poisson regression, zero-inflated models, etc. In this ...

There are many machine learning techniques that can be used for a binary classification problem; one of the simplest is called logistic regression. And there are many ways to train a logistic ...

Compared to separate binary regression models, one of the advantages of ordinal logistic regression is that it includes fewer unknown quantities, here odds ratios, in the model. This results in a ...

Logistic regression can be binomial, ordinal or multinomial. Binomial or binary logistic regression deals with situations in which the observed outcome for a dependent variable can have only two ...

Course Topics"Logistic and Poisson Regression," Wednesday, November 5: The fourth LISA mini course focuses on appropriate model building for categorical response data, specifically binary and count ...