Devdiscourse

New AI forecasting model promises greater stability for Kenya’s volatile food prices

Kenya’s food markets are known for extreme volatility influenced by weather shocks, inflation, currency fluctuations, and ...
Tobacco Control

Gendered educational disparities and in-home smoking and use of electronic tobacco/nicotine ...

Background Smoke-free and aerosol-free households (SAFHs) reduce exposure to secondhand smoke and aerosol and support ...
IEEE

Multi-Task Semantic Genetic Programming With Reinforcement Learning for Multi-Output ...

Abstract: Multi-output symbolic regression involves predicting two or more target variables simultaneously, adding complexity compared to single-output symbolic regression due to the interdependence ...
Frontiers

Absorbent material composition prediction based on multi-objective regression with value ...

1 College of Computer Engineering, Jimei University, Xiamen, Fujian, China 2 China-Belarus “Belt and Road” Electromagnetic Environmental Effects Laboratory, China Electronics Technology Group ...
Visual Studio Magazine

Linear Support Vector Regression Using C# with Particle Swarm Training

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 ...
IEEE

Multi-Output Regression for the Prediction of World-Class Performances in Women’s Handball

Abstract: The purpose of this study was to investigate the relationship between workload and in-game technical and athletic performance. To achieve this,A modeling approach that predicts multiple ...
Visual Studio Magazine

Linear Support Vector Regression from Scratch Using C# with Evolutionary Training

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 ...
GitHub

multiple-output-regression

This repository provides R functions to compute distorted M-quantiles, central regions, and depth functions for multivariate data, extending to multiple output regression settings.
Frontiers

Neural network-based performance prediction of marine UHPC with coarse aggregates

In order to improve bearing capacity and service life of marine structure using marine UHPC with coarse aggregate (UHPC-CA), it is necessary to reasonably predict the performance of UHPC-CA. The ...