1 / 4

Retraining of the SAMANN Network

Retraining of the SAMANN Network. Viktor Medvedev , Gintautas Dzemyda {Viktor.m, Dzemyda}@ktl.mii.lt Institute of Mathematics and Informatics Vilnius, Lithuania. 32nd International Conference on Current Trends in Theory and Practice of Computer Science Student Research Forum

fawn
Download Presentation

Retraining of the SAMANN Network

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Retraining of the SAMANN Network Viktor Medvedev, Gintautas Dzemyda {Viktor.m, Dzemyda}@ktl.mii.lt Institute of Mathematics and Informatics Vilnius, Lithuania 32nd International Conference on Current Trends in Theory and Practice of Computer Science Student Research Forum January 21 - 27, 2006 Merin, Czech Republic SOFSEM 2006, SRF

  2. Key words: visualization, multidimensional data, Sammon’s mapping, SAMANN neural network, retraining of the network • Multidimensional data.Observations from real-world problems are often highdimensionalvectors. The problem is to discover knowledge in the set of multidimensional points. • Visualization is a powerful tool in data analysis. It makes easier the understandability and perception of data. • Sammon’s mapping, multidimensional scaling, principal components • Sammon‘s mapping – a well-known procedure for mapping data from a high-dimensional space onto a lower-dimensional one. • A neural network for sammon’s projection SOFSEM 2006, SRF

  3. SAMANN – a specific backpropagation algorithm to train a multilayer feed-forward artificial neural network (SAMANN) to perform the Sammon‘s nonlinear projectionin an unsupervised way. • The network is able to project new patterns after training. • Retraining of the network. While working with large data amounts there may appear a lot of new vectors. • Strategies for retraining the network. Some strategies for retraining the network that realizes multidimensional data visualization have been proposed. • One of the proposed strategies enables us to attain good visualization results in a very short time as well as to get smaller visualization errors and to improve the accuracy of projection as compared to other strategies. SOFSEM 2006, SRF

  4. Thank you for your attention SOFSEM 2006, SRF

More Related