Approximate Entropy Reducts 论文
2002Fundamenta Informaticae引用 272
Rough Sets and Fuzzy LogicReservoir Engineering and Simulation MethodsBayesian Modeling and Causal Inference
详细信息
- 发表期刊/会议
- Fundamenta Informaticae
- 发表日期
- 2002-01-01
- 发表年份
- 2002
关键词
Rough Sets and Fuzzy LogicReservoir Engineering and Simulation MethodsBayesian Modeling and Causal Inference
摘要
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.