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A hierarchically growing hyperbolic self-organizing map for rapid structuring of large data sets
| Content Provider | Semantic Scholar |
|---|---|
| Author | Ontrup, Jörg Ritter, Helge Dr. |
| Copyright Year | 2005 |
| Abstract | We introduce the Hierarchically Growing Hyperbolic Self-Organizing Map (H2SOM) featuring two extensions of the HSOM (hyperbolic SOM): (i) a hierarchically growing variant that allows for incremental training with an automated adaptation of lattice size to achieve a prescribed quantization error and (ii) an approximate best match search that utilizes the special structure of the hyperbolic lattice to achieve a tremendous speed-up for large map sizes. Using the MNIST database as a benchmark dataset, we show that the H2SOM yields a highly efficient visualization algorithm that combines the virtues of the SOM with extremely rapid training and low quantization & classification errors. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://ni.www.techfak.uni-bielefeld.de/files/OntrupRitter2005-AHG.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |