2026 Section 2 baseball postseason predictions for every classification

The six brackets for the 2026 Section 2 baseball tournament were released Monday. Just two of the six area fields a year ago ...
Visual Studio Magazine

Multi-Class Classification Using LightGBM

Dr. James McCaffrey of Microsoft Research provides a full-code, step-by-step machine learning tutorial on how to use the LightGBM system to perform multi-class classification using Python and the ...
The New York Times

5 Steps to Solve (Almost) Any Problem

You probably don’t need more time. By Jancee Dunn When I look back on all the major decisions I’ve dithered over, I could scream. It took me a decade to commit to becoming a parent. I wavered for a ...
C&EN

Addressing Imbalanced Classification Problems in Drug Discovery and Development Using Random Forest, Support Vector Machine, AutoGluon-Tabular, and H2O AutoML

The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.
IEEE

Multiview Classification Through Learning From Interval-Valued Data

Abstract: The classification problem concerning crisp-valued data has been well resolved. However, interval-valued data, where all of the observations’ features are described by intervals, are also a ...
Visual Studio Magazine

Binary Classification Using LightGBM

Dr. James McCaffrey from Microsoft Research presents a full-code, step-by-step tutorial on using the LightGBM tree-based system to perform binary classification (predicting a discrete variable that ...
The National Interest

The Classification Problem: Can the CIA Defeat Its Greatest Internal Enemy?

In a world of rapid change and geopolitical turbulence, intelligence services are an important weapon in a policymaker’s arsenal. When it comes to human intelligence, the Central Intelligence Agency ...
IEEE

Visually Interpretable Fuzzy Neural Classification Network With Deep Convolutional Feature Maps

Abstract: This article proposes a deep feature map-based fuzzy neural classification network (DFM-FNCN) with applications to shape-based classification problems. The DFM-FNCN is characterized by ...