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

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 ...
GitHub

QwQ2000/TheWebConf24-LTGNN-PyTorch

TheWebConf'24 full paper - "Linear-Time Graph Neural Networks for Scalable Recommendations" - QwQ2000/TheWebConf24-LTGNN-PyTorch ...
IEEE

Kernel Ridge Regression for Generalized Graph Signal Processing

Abstract: In generalized graph signal processing (GGSP), a function (an element from a separable Hilbert space) is associated with each vertex. To perform non-linear filtering and regression under the ...