A new turbulence equation for eddy interactions: AI and physics team up to tackle notoriously difficult question

The currents of the oceans, the roiling surface of the sun, and the clouds of smoke billowing off a forest fire—all are ...
Mises Institute

Are There Constants in Economics?

One of the Austrian arguments against using mathematics to model economic phenomena is that there are no constants in ...
Visual Studio Magazine

Linear Regression with Pseudo-Inverse Training Using JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
Frontiers

Handling missing data of using the XGBoost-based multiple imputation by chained equations regression method

1 Shangwan Coal Mine, Ejin Horo Banner, Ordos, China 2 CCTEG Xi’an Research Institute Co. Ltd., Xi’an, China This study introduces an XGBoost-MICE (Multiple Imputation by Chained Equations) method for ...
technologynetworks

Linear Regression

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 ...
Simon Fraser University

Lesson 10 Multiple Linear Regression

The purpose of this tutorial is to continue our exploration of regression by constructing linear models with two or more explanatory variables. This is an extension of Lesson 9. I will start with a ...
IEEE

Symbolic Regression for Discovery of Medical Equations: A Case Study on Glomerular Filtration Rate Estimation Equations

Abstract: Symbolic Regression (SR) is a sub-field of machine learning that attempts to find a concise closed-form equation for regression tasks. The main strength of SR is in discovering new equations ...