Zheng Yuan, Yuhong Yang, Combining Linear Regression Models: When and How?, Journal of the American Statistical Association, Vol. 100, No. 472 (Dec., 2005), pp. 1202-1214 ...

We study a model mixing method for estimating the linear function in a partially linear regression model and derive oracle inequalities that show the mixed estimators perform nearly as well as the ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...

Before building my model, I want to step back to offer an easy-to-understand definition of linear regression and why it’s vital to analyzing data. What is linear regression?

In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

Multiple linear regression. Multiple linear regression models are much more complicated and can work with a greater number of lines and shapes on charts.

Course TopicsLinear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the ...

In several recent regression problem contests, LightGBM entries did very well. This may be due, in part, to the fact that LightGBM can be used out-of-the-box, which leaves a lot of time for ...