Visual Studio Magazine

Data Clustering Using Entropy Minimization

Entropy Minimization is a new clustering algorithm that works with both categorical and numeric data, and scales well to extremely large data sets. Data clustering is the process of placing data items ...
JSTOR Daily

Clustering Huge Number of Financial Time Series: A Panel Data Approach With High-Dimensional Predictors and Factor Structures

This article Introduces a new procedure for clustering a large number of financial time series based on high-dimensional panel data with grouped factor structures. The proposed method attempts to ...
Mena FN

Applying HDBSCAN Clustering To Filter B2B Databases: How Z&S Consulting Is Bringing Data Science To Lead Generation

(MENAFN- Newsfile Corp) Mexico City, Mexico--(Newsfile Corp. - September 30, 2024) - Z&S Consulting today announced the implementation of the HDBSCAN (Hierarchical Density-Based Spatial Clustering of ...
Network World

Virtualization and clustering: combining two winning strategies

Virtualization and clustering can be two faces of the same coin. Computing virtualization is a very hot topic for data center managers. Whether the motivation is higher utilization, reduced management ...

Potentially distinct structure in Kuiper belt discovered with help of clustering algorithm

A vast region of our solar system, called the Kuiper belt, stretches from the orbit of Neptune out to 50 or so astronomical units (AU), where an AU is the distance between Earth and the sun. This ...