Cluster Analysis

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Information about Cluster Analysis

Published on October 17, 2011

Author: kittukind


A SEMINAR ON CLUSTER ANALYSIS: 11- 1 A SEMINAR ON CLUSTER ANALYSIS S.Sai Krishna III-MCA 10030 What is Clustering?: What is Clustering? Cluster analysis or clustering is the task of assigning a set of objects into groups the objects in the same cluster are more similar An Example: 11- 3 An Example Before Clustering After Clustering Clusters and clustering’s : 11- 4 Clusters and clustering’s The notion of a cluster varies between algorithms We’ve to choose one of the many decisions to take when choosing the appropriate algorithm for a particular problem The clusters found by different algorithms vary significantly in their properties cluster models : 11- 5 cluster models Connectivity models Centric models Distribution models Density models Requirements of Clustering in Data Mining : 11- 6 Requirements of Clustering in Data Mining Ability to deal with different types of attributes Ability to deal with noisy data High dimensionality Interpretability and usability Cluster Algorithms : 11- 7 Cluster Algorithms Hierarchical clustering Centric-based clustering Distribution-based clustering Density-based clustering Evaluation of Clustering Results : 11- 8 Evaluation of Clustering Results Internal evaluation External evaluation Internal evaluation : 11- 9 Internal evaluation When a clustering result is evaluated based on the data that was clustered itself, this is called internal evaluation These methods usually assign the best score to the algorithm that produces clusters External evaluation : 11- 10 External evaluation In external evaluation, clustering results are evaluated based on data that was not used for clustering consist of a set of pre-classified items, and these sets are often created by human (experts) Applications: : 11- 11 Applications: Plant and animal ecology Sequence analysis Medical imaging Social network analysis Computer science Advanced Technology Cluster  : 11- 12 Advanced Technology Cluster In general, advanced technology clusters differ from branch specific clusters Examples of clusters are IT, advanced material, energy clusters, micro technology e.t.c Conclusion and Cautions : 11- 13 Conclusion and Cautions Cluster analysis methods will always produce a grouping The groupings produced by cluster analysis may or may not prove useful for classifying objects But the Casual work of Clustering gives an Equal Misleads!

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