Journal
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
Volume 2, Issue 3, Pages 135-145Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s13042-011-0028-x
Keywords
Information generalization; Data mining; Knowledge discovery; Decision tree; Production rules; Model of information noise; Learning sample
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Funding
- RFBR [09-01-00076a]
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The problem of information generalization for real data that may contain noisy data is considered. Various models of information noise are presented, and the influence of noise to the algorithms of generalization is discussed. We used the methods of constructing decision trees and forming production rules. The results of the modeling are presented.
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