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What is Cluster Validity Measures

Handbook of Research on Artificial Immune Systems and Natural Computing: Applying Complex Adaptive Technologies
Indices to measure the quality of clustering obtained. When the correct classification is known, SSE measure (sum of square of errors) or accuracy can be used. If it is not known, other measures can used, such as Davies-Bouldin index, Dunn Index, Silhouette index, Mutual information, etc.
Published in Chapter:
Ant Colonies and Data Mining
Miroslav Bursa (Czech Technical University in Prague, Czech Republic) and Lenka Lhotska (Czech Technical University in Prague, Czech Republic)
DOI: 10.4018/978-1-60566-310-4.ch019
Abstract
The chapter concentrates on the use of swarm intelligence in data mining. It focuses on the problem of medical data clustering. Clustering is a constantly growing area of current research. Medicine, market, trade, and meteorology belong to the numerous fields that benefit of its techniques. First an introduction into data mining and cluster validation techniques is presented, followed by a review of ant-inspired concepts and applications. The chapter provides a reasonably deep insight into the most successful ant colony and swarm intelligence concepts, their paradigms and application. The authors present discussion, evaluation and comparison of these techniques. Important applications and results recently achieved are provided. Finally, new and prospective future directions in this area are outlined and discussed.
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