Probabilistic approaches to rough sets

By Yiyu Yao. Expert Syst. J. Knowl. Eng., 2003

342 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics, Information Systems

View Paper: https://www.semanticscholar.org/paper/99a9e378e66ddf187ae96afcdf6ffcbbd72f1f83

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Dominik Lzak
2. Georg Peters
3. Pawan Lingras
4. Yan Zhao
5. Yiyu Yao
6. Witold Pedrycz
7. Richard Jensen
8. Qiang Shen

In Computational Theory and Mathematics

1. Dominik Lzak
2. Georg Peters
3. Pawan Lingras
4. Yan Zhao
5. Yiyu Yao
6. Witold Pedrycz
7. Richard Jensen
8. Qiang Shen

In Information Systems

1. Dominik Lzak
2. Georg Peters
3. Pawan Lingras
4. Yan Zhao
5. Yiyu Yao
6. Richard Jensen
7. Qiang Shen

Citations in the corpus

• Decision-Theoretic Rough Set Models (2007, background): “In fact, they produce the same rough set approximations [29, 30].”
• A Partition Model of Granular Computing (2004, methodology): “The cardinality of a granule, or Hartley information measure, can be used as a measure of the size or uncertainty of a granule [64].”
• Attribute reduction in decision-theoretic rough set models (2008, methodology): “The proposals include probabilistic rough set models [12,20,28,40,44,45,53,54], decision-theoretic rough set models [43,47,48], variable precision rough set models [21,52], rough membership functions [25], parameterized rough set models [27,30,34], and Bayesian rough set models [8,9,32,33].”
• Rudiments of rough sets (2007, neutral): “, [78,297,338,358,379,367,375]).”
• Probabilistic rough set approximations (2008, methodology): “At the same time, it seems necessary to provide a unified and comprehensive framework so that those results can be put together into an integrated whole, rather than separated studies [54].”
• An Outline of a Theory of Three-Way Decisions (2012, background): “A main advantage of a DTRS model is its solid foundation based on Bayesian decision theory.”
• Three-Way Decision: An Interpretation of Rules in Rough Set Theory (2009, methodology): “Based on the well established Bayesian decision procedure, the decisiontheoretic rough set model provides systematic methods for deriving the most suitable thresholds on probabilities for defining the three regions [14,16,17,18].”
• Rough Sets: Selected Methods and Applications in Management and Engineering (2012, methodology): “Recently various soft computing methodologies (like fuzzy logic, neural networks, genetic algorithms and rough sets) have been applied to handle the different challenges posed by data mining [10], involving large heterogeneous datasets.”
• Three-way decisions with probabilistic rough sets (2010, methodology): “Given the loss matrix, the expected losses associated with taking different actions for objects in [x] can be expressed as [34,40,41]:”