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 ...

Some results are presented on improving the fit of the logistic regression model for binary data by transforming the vector of explanatory variables. The methods are based on consideration of the ...

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 ...

Basic logistic regression classification is arguably the most fundamental machine learning (ML) technique. Basic logistic regression can be used for binary classification, for example predicting if a ...

Marginal models for multivariate binary data permit separate modelling of the relationship of the response with explanatory variables, and the association between pairs of responses. When the former ...

The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to see if there's a relationship between two variables, with the first known ...

Course TopicsIn this short course we will cover how to analyze simple and multiple linear regression models. You will learn concepts in linear regression such as:1) How to use the F-test to determine ...