A new outlier detection base on the self-organizing map algorithm

This article applies the method of artificial neural networks in the outlier detection, and gives one kind of new outlier detection method. According to the thoughts of the GHSOM algorithm and the GHTSOM algorithm, we make the improvement to the SOM algorithm. The improvement algorithm can be applie...

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Vydáno v:	Chinese Control Conference s. 3944 - 3949
Hlavní autoři:	Feng Xiangdong, Li Yueshan, Ma Zhiyuan
Médium:	Konferenční příspěvek
Jazyk:	čínština angličtina
Vydáno:	TCCT, CAA 01.07.2013
Témata:	Abstracts Artificial neural networks Educational institutions Electronic mail Growing hierarchical self-organizing map algorithm Growing hierarchical tree self-organizing map algorithm Kernel Outlier detection Self-organizing map algorithm Support vector machines
ISSN:	1934-1768
On-line přístup:	Získat plný text
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Popis
Shrnutí:	This article applies the method of artificial neural networks in the outlier detection, and gives one kind of new outlier detection method. According to the thoughts of the GHSOM algorithm and the GHTSOM algorithm, we make the improvement to the SOM algorithm. The improvement algorithm can be applied in the outlier detection, and this dissertation gives the different outlier detection examples and analyze the algorithm performance and the expansion ability, the performance is quite stable and adaptation is quite strong to the different date. Compares with the outlier detection use support vector machines, this method doesn't need to choose the kernel function and adjust the parameter unceasingly, and it has very good adaptation to the change of the data distribution.
ISSN:	1934-1768