New JWST images of abnormally well-developed galaxy cluster open up the 'cosmic noon' frontier

A stunningly concentrated and hefty galaxy cluster, from a time in the universe's history when such massive structures aren't ...
Nature

A new possibilistic-based clustering method for probability density functions and its application to detecting abnormal elements

Cluster analysis can also detect abnormalities besides building a basis for identifying elements into clusters. Detecting abnormalities is a highly developed feature in the field of unsupervised ...
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 ...
Visual Studio Magazine

Clustering Mixed Categorical and Numeric Data Using k-Means with C#

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on a "very tricky" machine learning technique. Data clustering is the process of grouping data items together so ...
Nature

Deep embedded clustering generalisability and adaptation for integrating mixed datatypes: two critical care cohorts

We validated a Deep Embedded Clustering (DEC) model and its adaptation for integrating mixed datatypes (in this study, numerical and categorical variables). Deep Embedded Clustering (DEC) is a ...