Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...

The adjusted r-squared is helpful for multiple regression and corrects for erroneous regression, giving you a more accurate correlation coefficient. If you look at the multiple regression we did, ...

All of the predictive methods implemented in PROC PLS work essentially by finding linear combinations of the predictors (factors) to use to predict the responses linearly. The methods differ only in ...

It can be highly beneficial for companies to develop a forecast of the future values of some important metrics, such as demand for its product or variables that describe the economic climate. There ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric ...

During the course of operation, businesses accumulate all kinds of data such as numbers related to sales performance and profit, and information about clients. Companies often seek out employees with ...

ABSTRACT There are a variety of multivariate statistical methods for analyzing the relations between two datasets. Two commonly used methods are canonical correlation analysis (CCA) and maximum ...

High-dimensional data analysis has been an active area, and the main focus areas have been variable selection and dimension reduction. In practice, it occurs often that the variables are located on an ...