Tentacled Self-Organizing Map for Effective Data Extraction

— Since we can accumulate a huge amount of data including useless information in these years, it is important to investigate various extraction method of clusters from data including a lot of noises. The Self-Organizing Map (SOM) attracts attentions for clustering in these years. In our past study, we have proposed a method of using simultaneously two kinds of SOMs whose features are different (ÒSOM), namely, one selforganizes the area on which input data are concentrated, and the other self-organizes the whole of the input space. Further, we have applied this method to clustering of data including a lot of noises and have confirmed the efficiency. However, in order to obtain an efficient clustering performance using this method, we must determine the appropriate number of the SOMs used in the method. This problem has been remedied by proposing the Peace SOM (PSOM) method, however, PSOM algorithm must be used after executing the ÒSOM method. In this study, we propose a method of...

• Type: Conference
• Year: 2006
• Where: IJCNN
• Authors: Haruna Matsushita, Yoshifumi Nishio
• Keywords: Efficient Clustering Performance, IJCNN 2006, Input Data, Various Extraction Method