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 ...

Just as we might consult multiple experts about a problem and then combine their advice to come to a consensus decision, repeated statistical analyses on the same data can be combined to form a single ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of decision tree regression using the C# language. Unlike most implementations, this one does not use recursion ...

The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict the annual income of a person based on their sex (male or female), age, ...

This is a preview. Log in through your library . Abstract Bayesian Additive Regression Trees (BART) is a flexible machine learning algorithm capable of capturing nonlinearities between an outcome and ...