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.

• Type: Journal
• Year: 2002
• Where: FUIN
• Authors: Dominik Slezak
• Keywords: Approximate Entropy Reduction, Entropy, FUIN 2002, Information Entropy Measure