Educational Implementation · Jupyter Notebook

advanced-clustering

Comparative study of K-Means, DBSCAN, Hierarchical, and Spectral Clustering on three benchmark datasets — with proper diagnostics (ARI, silhouette, dendrograms, k-distance, parameter sensitivity).

Pop Alexandru@pop123-ux · Atlas 70.7 · #4= builder

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What it is

The repository provides a comparative study of K-Means, DBSCAN, hierarchical, and spectral clustering on synthetic datasets, accompanied by a Jupyter notebook and a script to regenerate all figures.

Scored from the code at its last scan, 8 Oct 2026. How merit is scored

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Machine Learning90%
Data Science20%

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39advanced-clusteringEducational Implementation · Jupyter Notebook46.5/100ImplementationPop AlexandruMachine Learning
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What it is

Where it counts

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