A Self-Organizing Neural Network for Detecting Novelties

被引：0

作者：

Albertini, Marcelo Keese ^{[1
]}

de Mello, Rodrigo Fernandes ^{[1
]}

机构：

[1] Univ Sao Paulo, Inst Ciencias Matemat & Computacao, Dept Ciencias Computacao, BR-05508 Sao Paulo, Brazil

来源：

APPLIED COMPUTING 2007, VOL 1 AND 2 | 2007年

关键词：

novelty detection; self-organizing neural networks;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In order to detect new events, a system must support on-line learning, adapting to pattern dynamic characteristics. Studies of such adaptation have originated the novelty detection area, which aims at identifying unexpected or unknown patterns. These researches have motivated this work to propose the on-line and unsupervised Self-Organizing Novelty Detection (SONDE) neural network. In this network, the creation of new neurons points out novelties. Experiments evaluated the influence of SONDE parameters and their capability to detect novelty events. These evaluations considered the datasets Biomed, ALL-AML Leukemia and DLBCL. Results are compared to others from GWR.

引用

页码：462 / 466

页数：5

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