A Novel Method for Visualization of Clustering Results

Autor:	Chao Gao, Caiya Zhang
Rok vydání:	2010
Předmět:	Statistics and Probability Fuzzy clustering business.industry Correlation clustering Pattern recognition Data structure Visualization Sammon mapping CURE data clustering algorithm Modeling and Simulation Statistics Fermat point Artificial intelligence Cluster analysis business Algorithm Mathematics
Zdroj:	Communications in Statistics - Simulation and Computation. 39:1049-1056
ISSN:	1532-4141 0361-0918
DOI:	10.1080/03610911003778101
Popis:	Sammon mapping is an approach of nonlinear dimension reduction and can be used for visualization. To avoid numerical complexity of the algorithm of traditional Sammon mapping, Kovacs and Abonyi (2004) proposed a modified Sammon mapping method. However, this improvement can only be applied to fuzzy clustering results. By using the property of Fermat point, we develop a new method in this article that can be applied to any clustering results. Different from other methods of visualization, we transfer information of clustering results into concentric circles around the Fermat points. So our procedure can demonstrate the data structure in a more informative way and the clustering results become easier to understand, especially for nonprofessionals. The effectiveness of the proposed method is studied by application to a real data in this article.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::9de2a49af105a8a86f99c6009c9fbd22 https://doi.org/10.1080/03610911003778101 Zobrazit plný text záznamu