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 ...
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 ...
Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...
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