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Problem of knowledge discovery in noisy databases

被引：0
|
作者：
Vadim Vagin
Marina Fomina
机构：
[1] Moscow Power Engineering Institute (Technical University),
来源：
International Journal of Machine Learning and Cybernetics | 2011年 / 2卷
关键词：
Information generalization; Data mining; Knowledge discovery; Decision tree; Production rules; Model of information noise; Learning sample;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
引用
收藏
页码：135 / 145
页数：10
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