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FUIN
2002

Approximate Entropy Reducts

13 years 3 months ago
Approximate Entropy Reducts
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 approximatelypreserves 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.
Dominik Slezak
Added 19 Dec 2010
Updated 19 Dec 2010
Type Journal
Year 2002
Where FUIN
Authors Dominik Slezak
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