Variable Precision Rough Set Model
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Summary
A generalized model of rough sets called variable precision model (VP-model), aimed at modelling classification problems involving uncertain or imprecise information, is presented and the main concepts are introduced formally and illustrated with simple examples.
- Type
- article
- Published
- 1993-02-01
- Cited by
- 2,066
- References
- 31
- OpenAlex
- https://openalex.org/W1997362234
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:15560782
Keywords
Rough set, Simple (philosophy), Variable (mathematics), Computer science, Representation (politics)
References
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- Syntactic Decision Procedures in Information Systems
- An Expert System for Conceptual Schema Design: A Machine Learning Approach
- Knowledge acquisition under uncertainty — a rough set approach
- Comparison of Rough-Set and Statistical Methods in Inductive Learning
- An introduction to probability, decision, and inference
- A machine learning approach in information retrieval
- Pattern classification and scene analysis
- Rough Classification of Patients After Highly Selective Vagotomy for Duodenal Ulcer
- An Introduction to Probability, Decision, and Inference
- Proceedings 1997 27th International Symposium on Multiple- Valued Logic
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- Structure-Based Attribute Reduction in Variable Precision Rough Set Models
- Automated Discovery of Medical Expert System Rules from Clinical Databases Based on Rough Sets
- Fuzzy and rough sets
- An inquiry into vaguenes and uncertainty
- Recognition of the type of vehicle and the road obstacle in optimized HRWD-PNN based image processing system
- Data mining tasks and methods: Rule discovery: rough set approaches for discovering rules and attribute dependencies
- Current State of Data Mining
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- Multigranulation Decision-theoretic Rough Set in Ordered Information System
- Automated knowledge acquisition from clinical databases based on rough sets and attribute-oriented generalization
- Interval and Fuzzy Techniques in Business-Related Computer Security: Intrusion Detection, Privacy Protection
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- Rough Set Extensions for Feature Selection
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