IEEE

Performance of Classification Algorithms Under Class Imbalance: Simulation and Real-World Evidence

Abstract: Class imbalance is a persistent challenge in machine learning, particularly in high-stakes applications such as medical diagnostics, bioinformatics, and fraud detection, where the minority ...
BioSpace

Engitix Announces Strategic Collaboration with GSK to Advance First-in-Class Targets for Liver Fibrosis Regression

Collaboration leverages Engitix’s human ECM Platform to identify high-confidence targets for liver fibrosis regression LONDON, June 08, 2026 (GLOBE NEWSWIRE) -- Engitix Ltd. (“Engitix”), a ...
LinkedIn

Logistic Regression: The Gateway to Modern Deep Learning Concepts

Despite its name, Logistic Regression is primarily used for classification problems, not regression. Why Logistic Regression Instead of Linear Regression? Linear Regression predicts outputs using a ...
IEEE

Deep Learning Framework for Multi-Class Noise Classification in Mid-Infrared Supercontinuum Generation

Abstract: Supercontinuum generation (SCG) is a nonlinear phenomenon that is highly sensitive to noise. Noise can cause spectral fluctuations that degrade coherence and stability in practical ...
Visual Studio Magazine

AdaBoost.R2 Regression Using C#

AdaBoost.R2 regression is a machine learning technique used to predict a single numeric value. AdaBoost.R2 builds a sequence of decision tree regressors where each accepted tree improves prediction ...