Question

18. Which of the following is not
true about the DBSCAN algorithm?
* 1 point A. It is a density based
clustering algorithm B. It requires
two parameters MinPts and epsilon
C. The number of clusters need to
be specified in advance D. It can
produce non-convex shaped clusters
11:43 am​

Answer 1

Explanation:

why is the government not the same in a state that has been the most popular of those who has been elected in a

Answer 2

The right response is (d) It can produce non-convex shaped clusters

• Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is a base calculation for thickness-based bunching.
• It can find bunches of various shapes and sizes from a lot of information, which is containing clamor and exceptions.
• It can track down inconsistent formed groups and bunches with commotion (for example exceptions).
• The primary thought behind DBSCAN is that a point has a place with a group assuming it is near many focuses from that bunch.
• The rule of DBSCAN is to observe the neighborhoods of information focuses surpasses specific thickness edge.
• The thickness edge is characterized by two boundaries: the range of the area (eps) and the base number of neighbors/main items (mints) inside the sweep of the area.