Understanding the Least Squares Criterion for Accurate Data Fitting

Learn how the Least Squares Criterion determines the line of best fit for data analysis, enhancing predictive accuracy in finance, economics, and investing.
AZoM on MSN

Water determination in vast samples via KF titration

Volumetric Karl Fischer titration accurately determines water content in various samples, adhering to European Pharmacopoeia ...
Scientific Research Publishing

Financial Prediction Models in Banks: Combining Statistical Approaches and Machine Learning Algorithms ()

Felimban, R. (2025) Financial Prediction Models in Banks: Combining Statistical Approaches and Machine Learning Algorithms.
GitHub

Semi-Supervised Graph Imbalanced Regression

This is the code for SGIR, a semi-supervised framework for Graph Imbalanced Regression. Data imbalance is easily found in annotated data when the observations of certain continuous label values are ...
IEEE

Predicting miRNA-Disease Association Based on Improved Graph Regression

Abstract: Recently, as a growing number of associations between microRNAs (miRNAs) and diseases are discovered, researchers gradually realize that miRNAs are closely related to several complicated ...
GitHub

lukeyf/graphs-and-lines

This repository is the implementation of the following paper: Theoretical Insights into Line Graph Transformation on Graph Learning. This project is built on the BREC dataset which includes 400 pairs ...
IEEE

Regression Models With Graph-Regularization Learning Algorithms for Accurate Fault Location in Smart Grids

Abstract: This article focuses on the design of a hierarchical framework for locating faults in smart grids by resorting to only modal components of three-phase voltage measurements. The search space ...