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                                       Details for article 4 of 10 found articles
 
 
  Approximate Entropy Reducts
 
 
Title: Approximate Entropy Reducts
Author: Dominik Ĺšlezak
Appeared in: Fundamenta informaticae
Paging: Volume 53 (2003) nr. 3-4 pages 365-390
Year: 2003-07-11
Contents: We use information entropy measure to extend the rough set based notion of a reduct. We introduce the Approximate Entropy Reduction Principle (AERP). It states that any simplification (reduction of attributes) in the decision model, which approximately preserves its conditional entropy (the measure of inconsistency of defining decision by conditional attributes) should be performed to decrease its prior entropy (the measure of the model's complexity). We show NP-hardness of optimization tasks concerning application of various modifications of AERP to data analysis.
Publisher: IOS Press
Source file: Elektronische Wetenschappelijke Tijdschriften
 
 

                             Details for article 4 of 10 found articles
 
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