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

The study departs from conventional mean-based economic forecasting by focusing on quantile prediction, a technique that ...

A research team has developed advanced methodologies for predicting the aboveground biomass (AGB) of corn by integrating unmanned aerial vehicles (UAVs), multi-sensor data, and machine learning models ...

ABSTRACT: Accurate forecasting of the system marginal price (SMP) is crucial to improve demand-side management and optimize power generation scheduling. However, predicting the SMP is challenging due ...

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, ...

Oak Ridge Institute for Science and Education (ORISE), Hosted at U.S. Environmental Protection Agency, Athens, Georgia 30605, United States ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of linear regression with two-way interactions between predictor variables. Compared to standard linear ...

Abstract: The aim of this study is to support the optimization of material management and production planning in an enterprise through effective forecasting of production trends based on multiple ...

This lesson will be more of a code-along, where you'll walk through a multiple linear regression model using both statsmodels and scikit-learn. Recall the initial regression model presented. It ...

Background: The aim of the present study was to establish a predictive model to predict the peritoneal cancer index (PCI) preoperatively in patients with pseudomyxoma peritonei (PMP). Conclusion: This ...