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.

Dr. James McCaffrey of Microsoft Research demonstrates applying the L-BFGS optimization algorithm to the ML logistic regression technique for binary classification -- predicting one of two possible ...

Learn what is Logistic Regression Cost Function in Machine Learning and the interpretation behind it. Logistic Regression Cost function is "error" representation of the model.

The CATMOD procedure can perform linear regression and logistic regression of response functions for data that can be represented in a contingency table. See Chapter 5, "Introduction to Categorical ...

In this paper we discuss collapsibility of logistic regression coefficients over a background variable and present necessary and sufficient conditions for collapsibility.

Binomial (or binary) logistic regression analysis is useful for predicting the presence or absence of a characteristic or outcome based on values of a set of predictor variables, and is applicable ...

Multivariate adaptive regression splines (MARS) have useful features to effectively reduce the number of terms in a model.