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Unsupervised Machine Learning: Clustering Algorithms Quiz
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Unsupervised Machine Learning: Clustering Algorithms Quiz

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Questions and Answers

What is the main characteristic of DBSCAN algorithm?

  • It groups points based on their density within a specific radius (correct)
  • It clusters points based on their similarity
  • It is a centroid-based clustering algorithm
  • It operates by dividing the data into a pre-defined number of clusters

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

  • The minimum number of points within the neighborhood of a point for it to be considered a core point
  • The radius around a point (correct)
  • The maximum cluster size
  • The distance between the centroids of clusters

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

  • Points with at least a minPts number of points within a distance of eps
  • Points that belong to the cluster of the core point they are connected to
  • Points with varying density
  • Points that do not satisfy the minPts condition (correct)

    • What is a limitation of DBSCAN clustering?

    <p>It is sensitive to parameters (eps and minPts)</p> Signup and view all the answers

    What type of clusters does DBSCAN work best with?

    <p>Irregularly shaped clusters</p> Signup and view all the answers

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