Titlebook: Advances in Self-Organising Maps; Nigel Allinson,Hujun Yin,Jon Slack Conference proceedings 2001 Springer-Verlag London Limited 2001 Data

AMUSE

书目名称Advances in Self-Organising Maps影响因子(影响力)




书目名称Advances in Self-Organising Maps影响因子(影响力)学科排名




书目名称Advances in Self-Organising Maps网络公开度




书目名称Advances in Self-Organising Maps网络公开度学科排名




书目名称Advances in Self-Organising Maps被引频次




书目名称Advances in Self-Organising Maps被引频次学科排名




书目名称Advances in Self-Organising Maps年度引用




书目名称Advances in Self-Organising Maps年度引用学科排名




书目名称Advances in Self-Organising Maps读者反馈




书目名称Advances in Self-Organising Maps读者反馈学科排名

古董

树木心

https://doi.org/10.1007/978-1-4471-4048-1mize the differential entropies of the kernel outputs and, at the same time, to minimize the mutual information between these outputs. The learning scheme is based on . learning supplemented with a cooperative/competitive stage to achieve topographically-organized maps. As a potential application, we consider density estimation.

sphincter

Intellectual

Iva Bojic,Tomislav Lipic,Vedran Podobnike, we suggest a new version of SOM, using the supervised learning approach. We compare the supervised version and the unsupervised version of SOM-SD on a benchmark problem involving visual patterns. As may be expected, the supervised version is able to solve the classification problem using very compact networks.

myalgia

Lecture Notes in Computer Scienceto identify health inequality structure is critical. It is believed that health inequality analysis is a complex problem. Self- organisation mapping is therefore employed in this paper to analyse health inequalities based on a data set provided by the Centre for Disease Control and Prevention, USA (CDC).

Cocker

联邦

帽子

痛苦一生