Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

"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 data. The most ...

A class of conditional logistic regression models for clustered binary data is considered. This includes the polychotomous logistic model of Rosner (1984) as a special case. Properties such as the ...

The latest trends in software development from the Computer Weekly Application Developer Network. This is a guest post for the Computer Weekly Developer Network written by Yana Yelina in her role as ...

Dr. James McCaffrey from Microsoft Research presents a C# program that illustrates using the AdaBoost algorithm to perform binary classification for spam detection. Compared to other classification ...

In recent columns we showed how linear regression can be used to predict a continuous dependent variable given other independent variables 1,2. When the dependent variable is categorical, a common ...