Conference proceeding
Support vector machines with evolutionary interval neural networks for granular feature transformation in making effective biomedical data classification
2005 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING, VOLS 1 AND 2, v 1
01 Jan 2005
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Abstract
In this paper, we use new evolutionary interval neural networks to do granular feature transformation based on granular computing, neural computing and evolutionary computation to alleviate kernel's burden in Support Vector Machines (SVMs) and help SVMs learn knowledge effectively. Simulation results for three different medical data sets show that SVMs using the evolutionary interval neural networks are more effective than the traditional SVMs in terms of testing accuracy.
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Details
- Title
- Support vector machines with evolutionary interval neural networks for granular feature transformation in making effective biomedical data classification
- Creators
- B Jin - Georgia State UniversityY Q Zhang - Georgia State UniversityXHT Hu
- Contributors
- X H Hu (Editor)Q Liu (Editor)A Skowron (Editor)T Y Lin (Editor)R R Yager (Editor)B Zhang (Editor)
- Publication Details
- 2005 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING, VOLS 1 AND 2, v 1
- Conference
- 2005 IEEE International Conference on Granular Computing
- Publisher
- IEEE
- Number of pages
- 4
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000232157200036
- Scopus ID
- 2-s2.0-33845329530
- Other Identifier
- 991019201388704721
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- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Theory & Methods