Computer Science
University of Cumberlands Data Mining Clustering Concepts Analysis Paper

University of cumberlands

Question Description

I’m trying to study for my Computer Science course and I need some help to understand this question.

1)Explain the following types of Clusters:

Well-separated clusters

Center-based clusters

Contiguous clusters

Density-based clusters

Property or Conceptual

2)Define the strengths of Hierarchical Clustering and then explain the two main types of Hierarchical Clustering.

3)DBSCAN is a dentisy-based algorithm. Explain the characteristics of DBSCAN.

4)List and Explain the three types of measures associated with Cluster Validity.

5)In regards to Internal Measures in Clustering, explain Cohesion and Separation.

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Final Answer

Attached.

Running head: CLUSTERS

1

Clusters
Name of the student
Institution affiliations

CLUSTERS

2

Question 1

1.

Well-separated clusters

It is a group of pieces, and these pieces are closer to all other parts in a bunch than any part that
is not from cluster
2.

Centre-based clusters

The centre-based cluster is closer to the middle of the group than it is closer to other clusters
3.

Contiguous clusters

It is several points that are in a bunch that is closer to one or more other spots in the group than
to any marks which are not in the cluster.
4.

Density-based clusters

This cluster is a dense area of points, which is differentiated by low-density regions, from other
areas with high density. It is ...

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