Investopedia

Multiple Linear Regression (MLR): Definition, Uses, & Examples

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...
Nature

Incorporation of machine learning and deep neural network approaches into a remote sensing-integrated crop model for the simulation of rice growth

Machine learning (ML) and deep neural network (DNN) techniques are promising tools. These can advance mathematical crop modelling methodologies that can integrate these schemes into a process-based ...
Nature

A machine learning approach for efficient multi-dimensional integration

Many physics problems involve integration in multi-dimensional space whose analytic solution is not available. The integrals can be evaluated using numerical integration methods, but it requires a ...
Medical Xpress

Regression approach outperforms ML algorithms in predicting optimal surgical method in submucosal tumor patients

Submucosal tumors (SMTs) are usually found in the stomach and esophagus during an upper endoscopy. Submucosal tunneling endoscopic resection (STER) and non-tunneling endoscopic resection (NTER) are ...
Visual Studio Magazine

Random Neighborhoods Regression Using C#

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the random neighborhoods regression technique, where the goal is to predict a single numeric value. Compared ...
Visual Studio Magazine

Random Forest Regression Using C#

Random forest regression is a tree-based machine learning technique to predict a single numeric value. A random forest is a collection (ensemble) of simple regression decision trees that are trained ...