Problem of knowledge discovery in noisy databases
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.
knowledge discovery information generalization model of information noise decision tree production rules data mining learning sample