Mikhail Ju Moshkov*, Marcin Piliszczuk, Beata Zielosko

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingForeword/postscriptpeer-review

1 Scopus citations


The subject matter of this monograph is connected with the following two problems of data mining and knowledge discovery: Representation of knowledge, contained in a decision table, in a form which is convenient for understanding. The length of knowledge description is crucial in this case. Prediction of the value of decision attribute for a new object. The accuracy of prediction is the most important aspect of this problem. These two aims (short description and high accuracy) seem to be incompatible. However, it is known that classifiers with shorter description are often more precise. This monograph is one more confirmation of this fact.

Original languageEnglish (US)
Title of host publicationPartial Covers, Reducts and Decision Rules in Rough Sets
Subtitle of host publicationTheory and Applications
EditorsMikhail Moshkov, Beata Zielosko, Marcin Piliszczuk
Number of pages6
StatePublished - 2008

Publication series

NameStudies in Computational Intelligence
ISSN (Print)1860-949X

ASJC Scopus subject areas

  • Artificial Intelligence


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