Data and knowledge visualization with virtual reality spaces, neural networks and rough sets: Application to cancer and geophysical prospecting data
| Autor: | Julio J. Valdés, Enrique Romero, Alan J. Barton |
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| Rok vydání: | 2012 |
| Předmět: |
Artificial neural network
Computer science business.industry General Engineering Knowledge visualization Virtual reality neural networks computer.software_genre Machine learning Data type Computer Science Applications data and knowledge visualization Discriminative model data projection Artificial Intelligence visual data mining virtual reality rough sets Rough set Data mining Artificial intelligence Representation (mathematics) business computer Geophysical prospecting |
| Zdroj: | Expert Systems with Applications. 39:13193-13201 |
| ISSN: | 0957-4174 |
| Popis: | Visual data mining with virtual reality spaces is used for the representation of data and symbolic knowledge. High quality structure-preserving and maximally discriminative visual representations can be obtained using a combination of neural networks (SAMANN and NDA) and rough sets techniques, so that a proper subsequent analysis can be made. The approach is illustrated with two types of data: for gene expression cancer data, an improvement in classification performance with respect to the original spaces was obtained; for geophysical prospecting data for cave detection, a cavity was successfully predicted. |
| Databáze: | OpenAIRE |
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