#min-samples

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mediumAI-checkedClustering

Which statements about DBSCAN (hyperparameters eps, the neighbourhood radius, and min_samples) are true? Select all that apply.

With a tiny eps and min_samples = 1, DBSCAN is likely to put each point in its own cluster1
With a smaller eps and a larger min_samples, DBSCAN is likely to end up with one big cluster2
K-Means is more affected by outliers than DBSCAN3
In DBSCAN, every point in a cluster must itself have at least min_samples neighbours (itself included) within eps4

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