How-To Geek on MSN

Excel finally fixed its worst problems—but you're still using the old workarounds

Excel has quietly gained dynamic arrays, XLOOKUP, Power Query, and Python, yet many still work the old way.
Johns Hopkins Newsletter

Sohini Ramachandran discusses population genetics and computational clustering algorithms

Family has always been important to those working in population genetics. When Sohini Ramachandran was a postdoc, the issue of relatives in a dataset causing inaccurate results was considered a major ...
GitHub

[ENH] Adding KModes and KPrototypes clustering algorithms

The workflow I want to enable is a seamless and native experience for clustering categorical and mixed data: This integrates categorical clustering directly into the robust and familiar scikit-learn ...
Scientific Research Publishing

Wang, B.S., Wang, G.C. and Wei, Y.H. (2025) Improvement of the Cluster Number Determination Method Based on K-Means Algorithm. Statistics and Decision-Making, 41, 59-64.

ABSTRACT: As a highly contagious respiratory disease, influenza exhibits significant spatiotemporal fluctuations in incidence, posing a persistent threat to public health and placing considerable ...
IEEE

An Enhanced Density Peak Clustering Algorithm With Dimensionality Reduction and Relative Density Normalization for High-Dimensional Duplicate Data

Abstract: Cluster analysis is a fundamental method for studying big data problems, as it groups samples based on shared features. In cluster analysis, a particular class of big data problems is ...
IEEE

Density Peaks Clustering Algorithm Based on Neighborhood Radius and Membership Degree

Abstract: The density peaks clustering (DPC) algorithm is a density-based clustering method that effectively identifies clusters with uniform densities. However, if the datasets have uneven density, ...
techtimes

Leveraging Machine Learning Algorithms to Combat Fraud in Supply Chain Operations

Abstract: Fraud in supply chain operations poses significant risks to businesses, including financial losses, operational inefficiencies, and erosion of stakeholder trust. With the increasing ...