Summary and Future Directions

In this chapter we make a summary of how to optimize the K-means clustering algorithm based on evolutionary computing. The system is still missing a user interface to handle invalid user input. Parallel coordinates that may be used as a tool to visualize data in high-dimensional spaces is only given...

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Bibliographic Details
Published in:Computational Intelligence, Evolutionary Computing and Evolutionary Clustering Algorithms Vol. 1; no. 1; pp. 113 - 120
Main Author: Kristensen, Terje
Format: Book Chapter
Language:English
Published: United States Bentham Science Publishers 01.09.2016
Subjects:
Clustering metric
Overplotting
Invalid cluster structures
Parallel coordinates
PSO
ISBN:1681083000, 9781681083001
Online Access:Get full text
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Summary:In this chapter we make a summary of how to optimize the K-means clustering algorithm based on evolutionary computing. The system is still missing a user interface to handle invalid user input. Parallel coordinates that may be used as a tool to visualize data in high-dimensional spaces is only given a short introduction. In addition, Particle Swarm Optimization (PSO) is also mentioned to find global solutions to optimization problems.
ISBN:1681083000
9781681083001
DOI:10.2174/9781681082998116010011