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Library/ Machine Learning (Supervised + Unsupervised)/ Unsupervised Learning by Building (one technique, two mini projects)/ U02 · Build: Clustering — A: Customer Segmentation with RFM (Online Retail II) · B: Electricity Day Types

subtopic

DBSCAN and HDBSCAN

10 min applied10 min research1 curated resources

Choose eps with a k-distance plot; fit DBSCAN; then HDBSCAN; inspect noise points. Concepts: Density clusters; eps; min_samples; core/border/noise; arbitrary shapes Project A: Noise = unusual customers (e.g. one-off wholesale buyers) — compare with U04 ideas. Project B: Noise = unusual days (holidays, outages, data errors).

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DBSCAN and HDBSCAN · 1x1labs.ai