Density-Based Clustering
Domino Data Lab
DECEMBER 2, 2020
Compared to centroid-based clustering like k-means, density-based clustering works by identifying “dense” clusters of points, allowing it to learn clusters of arbitrary shape and identify outliers in the data. The anomalous points pull the cluster centroid towards them, making it harder to classify them as anomalous points. neighborhoods.
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