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.
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 ...
Frontiers

SeismoQuakeGNN: a hybrid framework for spatio-temporal earthquake prediction with transformer-enhanced models

Accurate predictions of earthquakes are crucial for disaster preparedness and risk mitigation. Conventional machine learning models like Random Forest, SVR, and XGBoost are frequently used for seismic ...
IEEE

Refining Time-Space Traffic Diagrams: A Simple Multiple Linear Regression Model

Abstract: A time-space (TS) traffic diagram, which presents traffic states in time-space cells with color, is an important traffic analysis and visualization tool. Despite its importance for ...
IEEE

Graph Neural Networks With Multiple Prior Knowledge for Multi-Omics Data Analysis

Abstract: With the development of biotechnology, a large amount of multi-omics data have been collected for precision medicine. There exists multiple graph-based prior biological knowledge about omics ...