Brief Review of Self-Organizing Maps
| Autor: | Dubravko Miljkovic |
|---|---|
| Přispěvatelé: | Petar Biljanović |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Self-organizing map Artificial neural network Computer science business.industry Competitive learning self-organizing maps neural networks clustering visualization classification 02 engineering and technology Space (commercial competition) Machine learning computer.software_genre Visualization 03 medical and health sciences 030104 developmental biology 0202 electrical engineering electronic engineering information engineering Feature (machine learning) 020201 artificial intelligence & image processing Artificial intelligence Cluster analysis business Representation (mathematics) computer |
| Zdroj: | MIPRO |
| Popis: | As a particular type of artificial neural networks, self-organizing maps (SOMs) are trained using an unsupervised, competitive learning to produce a low- dimensional, discretized representation of the input space of the training samples, called a feature map. Such a map retains principle features of the input data. Self-organizing maps are known for its clustering, visualization and classification capabilities. In this brief review paper basic tenets, including motivation, architecture, math description and applications are reviewed. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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