Clustering algorithms are a powerful form of AI that can be applied to business challenges from customer segmentation to fraud detection.

K-Means Algorithm, Influenza Transmission, Cluster Analysis, Urban Characteristics Share and Cite: Ye, S. (2025) Application ...

Facility location and clustering algorithms constitute a critical area of research that bridges optimisation theory and data analysis. Facility location techniques focus on the strategic placement ...

Clustering algorithms can be boiled down across many facets of the entire product range to create a smaller, more manageable set of components that form a data map.

Entropy Minimization is a new clustering algorithm that works with both categorical and numeric data, and scales well to extremely large data sets.

Available clustering algorithms work only with structured data and use medoids as parameter for clustering.

Clustering non-numeric -- or categorial -- data is surprisingly difficult, but it's explained here by resident data scientist Dr. James McCaffrey of Microsoft Research, who provides all the code you ...