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.

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 ...

This article presents a complete demo program for logistic regression, using batch stochastic gradient descent training with weight decay. Compared to other binary classification techniques, logistic ...

A logistic regression for these data is a generalized linear model with response equal to the binomial proportion r/n. The probability distribution is binomial, and the link function is logit.

Logistic regression enables you to investigate the relationship between a categorical outcome and a set of explanatory variables. The outcome, or response, can be dichotomous (yes, no) or ordinal (low ...

The authors argue that for the cross-sectional multiattribute approach to choice modeling, the multinomial logit is theoretically and empirically superior to the more commonly used regression approach ...

The teaching of logit regression analysis is much neglected in statistics courses within sociology. This is unfortunate since it is well-suited to so many data analysis situations within the ...