Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/38079
標題: A New Clustering Validity Index for Cluster Analysis Based on a Two-Level SOM
作者: Shieh, S.L.
廖宜恩
Liao, I.E.
關鍵字: self-organizing map
clustering
clustering validity index
self-organizing map
neural networks
projection
期刊/報告no:: Ieice Transactions on Information and Systems, Volume E92D, Issue 9, Page(s) 1668-1674.
摘要: Self-Organizing Map (SOM) is a powerful tool for the exploratory of clustering methods. Clustering is the most important task in unsupervised learning and clustering validity is a major issue in cluster analysis. In this paper, a new clustering validity index is proposed to generate the clustering result of a two-level SOM. This is performed by using the separation rate of inter-cluster, the relative density of inter-cluster, and the cohesion rate of intra-cluster. The clustering validity index is proposed to find the. optimal numbers of clusters and determine which two neighboring clusters can be merged in a hierarchical clustering of a two-level SOM. Experiments show that, the proposed algorithm is able to cluster data more accurately than the classical clustering algorithms which is based on a two-level SOM and is better able to find an optimal number of clusters by maximizing the Clustering validity index.
URI: http://hdl.handle.net/11455/38079
ISSN: 0916-8532
文章連結: http://dx.doi.org/10.1587/transinf.E92.D.1668
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