Discuss and provide an example of the fact that validation o

Discuss and provide an example of the fact that validation of clustering structures is the most difficult and frustrating part of cluster analysis.

Solution

Cluster validation is concerned with the quality of clusters generated by an algorithm for data clustering. Given the partitioning of a data set, it attempts to answer questions such as: How pronounced is the cluster structure that has been identified? How do clustering solutions from different algorithms compare? How do clustering solutions for different parameters (e.g. the number of clusters compare).Cluster analysis aims at identifying groups of similar objects and, therefore helps to discover distribution of patterns and interesting correlations in large data sets.

As validation of clustering structures is difficult because it is a complex process   based on the intrinsic properties of the data also the use of cluster analysis presents a complex challenge because it requires several methodological choices that determine the quality of a cluster solution