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13 lines
685 B
Plaintext
13 lines
685 B
Plaintext
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HDBSCAN - Hierarchical Density-Based Spatial Clustering of Applications with
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Noise. Performs DBSCAN over varying epsilon values and integrates the result to
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find a clustering that gives the best stability over epsilon. This allows
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HDBSCAN to find clusters of varying densities (unlike DBSCAN), and be more
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robust to parameter selection.
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In practice this means that HDBSCAN returns a good clustering straight away with
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little or no parameter tuning -- and the primary parameter, minimum cluster
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size, is intuitive and easy to select.
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HDBSCAN is ideal for exploratory data analysis; it's a fast and robust algorithm
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that you can trust to return meaningful clusters (if there are any).
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