Data clustering is the process of placing data items into groups so that items within a group are similar and items in different groups are dissimilar. The most common technique for clustering numeric ...

A k-means-type algorithm is proposed for efficiently clustering data constrained to lie on the surface of a p-dimensional unit sphere, or data that are mean-zero-unit-variance standardized ...

K-means is comparatively simple and works well with large datasets, but it assumes clusters are circular/spherical in shape, so it can only find simple cluster geometries. Data clustering is the ...

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 of ...

Business stakeholders are always looking for innovative ways to better understand customer behaviour in the current, data-driven marketing landscape. Unsupervised machine learning, which allows ...