Dr. James McCaffrey from Microsoft Research presents a complete end-to-end program that explains how to perform binary classification (predicting a variable with two possible discrete values) using ...

The data doctor continues his exploration of Python-based machine learning techniques, explaining binary classification using logistic regression, which he likes for its simplicity. The goal of a ...

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 ...

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 ...

"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 ...

Four new methods for classification of multivariate binary data are presented, based on an orthogonal expansion of the density in terms of discrete Fourier series. The performance of these methods in ...

Several approaches can be taken to predict case membership in the classes of a dependent variable. Classification and regression trees (CART) analysis has been cited repeatedly as a powerful ...