Data Mining Clustering Analysis - Basic Concepts and Algorithms Assignment

Dept. of Information Technology &
School of Computer and Information Sciences
University of the Cumberlands
Chapter 8 Assignment
Data Mining Clustering Analysis: Basic Concepts and Algorithms Assignment
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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Solution: Data Mining Clustering Analysis - Basic Concepts and Algorithms Assignment