Unsupervised Machine Learning: Clustering Algorithms Quiz

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What is the main characteristic of DBSCAN algorithm?

It groups points based on their density within a specific radius

What does the parameter 'Epsilon (eps)' determine in DBSCAN algorithm?

The radius around a point

What are 'Noise Points' in the context of DBSCAN algorithm?

Points that do not satisfy the minPts condition

What is a limitation of DBSCAN clustering?

It is sensitive to parameters (eps and minPts)

What type of clusters does DBSCAN work best with?

Irregularly shaped clusters

Test your knowledge of clustering algorithms such as DBSCAN, K-means, Spectral, and Hierarchical. Learn about the characteristics and best use cases of DBSCAN, a density-based clustering algorithm suitable for identifying irregularly shaped clusters, handling unknown cluster numbers, and datasets with noise.

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