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 ...

One key to efficient data analysis of big data is to do the computations where the data lives. In some cases, that means running R, Python, Java, or Scala programs in a database such as SQL Server or ...

Microsoft Research's Dr. James McCaffrey show how to perform binary classification with logistic regression using the Microsoft ML.NET code library. The goal of binary classification is to predict a ...

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 ...

Dr. James McCaffrey of Microsoft Research uses a full code program, examples and graphics to explain multi-class logistic regression, an extension technique that allows you to predict a class that can ...

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...

This course is compulsory on the MSc in Statistics (Social Statistics) and MSc in Statistics (Social Statistics) (Research). This course is available on the MSc in Data Science, MSc in Health Data ...