Abstract
Clustering is an essential tool in data mining that has drawn enormous attention. In this paper, we present a new clustering algorithm with the help of Voronoi diagram. Here the clusters are formed by considering the neighboring Voronoi cells. The points belong to the closer Voronoi cells are merged to form the clusters. The similarity of the points is measured based on Euclidean distance of the neighboring points and hence it is not necessary to compare the distances from one point to all other points of the given set. We perform various experiments using many synthetic and biological data sets. The experimental results demonstrate the significance of the proposed method.
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Edla, D.R., Jana, P.K. (2012). Clustering Biological Data Using Voronoi Diagram. In: Thilagam, P.S., Pais, A.R., Chandrasekaran, K., Balakrishnan, N. (eds) Advanced Computing, Networking and Security. ADCONS 2011. Lecture Notes in Computer Science, vol 7135. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29280-4_21
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DOI: https://doi.org/10.1007/978-3-642-29280-4_21
Publisher Name: Springer, Berlin, Heidelberg
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