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 ...

Discover how linear regression works, from simple to multiple linear regression, with step-by-step examples, graphs and real-world applications.

Logistic regression is a powerful technique for fitting models to data with a binary response variable, but the models are difficult to interpret if collinearity, nonlinearity, or interactions are ...

Linear and logistic regression models are essential tools for quantifying the relationship between outcomes and exposures. Understanding the mathematics behind these models and being able to apply ...

The log-logistic distribution has a non-monotonic hazard function which makes it suitable for modelling some sets of cancer survival data. A log-logistic regression model is described in which the ...

The Data Science Lab How to Do Kernel Logistic Regression Using C# Dr. James McCaffrey of Microsoft Research uses code samples, a full C# program and screenshots to detail the ins and outs of kernal ...

A new study investigated how logistic regression model training affects performance, and which features are best to include when examining datasets from individuals suffering from COVID-19.