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 ...

Dr. James McCaffrey presents a complete end-to-end demonstration of decision tree regression from scratch using the C# language. The goal of decision tree regression is to predict a single numeric ...

I predict you'll find this logistic regression example with R to be helpful for gleaning useful information from common binary classification problems. Logistic regression is a technique used to make ...

The short course will illustrate how to use JMP in linear regression analysis. The three main topics will be: Exploratory data analysis, simple liner regression and polynomial regression How to fit a ...

In Week 11, I explained the difference between anticipated regression and the so-called "Gambler's fallacy", and in Week 12, ...

A nonlinear regression model is applied to several sets of enzyme kinetics data, treating the entire regression vector as the parameter of interest. The resulting marginal posterior distributions are ...