Data Mining Clustering Analysis: Basic Concepts and Algorithms Assignment

 Note: submit  answers in proper APA paragraph format with references. 

     
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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