Journal ArticleDOI
Reducts within the variable precision rough sets model: A further investigation
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In this article, the authors investigated the criteria for a β-reduct within variable precision rough sets (VPRS) and suggested an additional condition for finding βreducts which assures a more general level knowledge equivalent to that of the full set of attributes.About:
This article is published in European Journal of Operational Research.The article was published on 2001-11-01. It has received 278 citations till now. The article focuses on the topics: Rough set & Set (abstract data type).read more
Citations
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Journal ArticleDOI
Semantics-preserving dimensionality reduction: rough and fuzzy-rough-based approaches
Richard Jensen,Qiang Shen +1 more
TL;DR: This paper reviews those techniques that preserve the underlying semantics of the data, using crisp and fuzzy rough set-based methodologies, and several approaches to feature selection based on rough set theory are experimentally compared.
Journal ArticleDOI
Attribute reduction in decision-theoretic rough set models
TL;DR: This paper addresses attribute reduction in decision-theoretic rough set models regarding different classification properties, such as decision-monotocity, confidence, coverage, generality and cost, and provides a new insight into the problem of attribute reduction.
Journal ArticleDOI
Information-preserving hybrid data reduction based on fuzzy-rough techniques
Qinghua Hu,Daren Yu,Zongxia Xie +2 more
TL;DR: An information measure is proposed to computing discernibility power of a crisp equivalence relation or a fuzzy one, which is the key concept in classical rough set model and fuzzy-rough set model, and a general definition of significance of nominal, numeric and fuzzy attributes is presented.
Journal ArticleDOI
Approaches to knowledge reduction based on variable precision rough set model
TL;DR: It is proved that for some special thresholds, β lower distribution reduct is equivalent to the maximum distribution reduction reduct, whereas β upper distribution reduCT is equivalents to the possible reduct.
Journal ArticleDOI
Review: Dimensionality reduction based on rough set theory: A review
K. Thangavel,A. Pethalakshmi +1 more
TL;DR: The rough sets hybridization with fuzzy sets, neural network and metaheuristic algorithms have been reviewed and the performance analysis of the algorithms has been discussed in connection with the classification.
References
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Book
Cluster Analysis
TL;DR: This fourth edition of the highly successful Cluster Analysis represents a thorough revision of the third edition and covers new and developing areas such as classification likelihood and neural networks for clustering.
Journal ArticleDOI
Rough sets
TL;DR: This approach seems to be of fundamental importance to artificial intelligence (AI) and cognitive sciences, especially in the areas of machine learning, knowledge acquisition, decision analysis, knowledge discovery from databases, expert systems, decision support systems, inductive reasoning, and pattern recognition.
Journal ArticleDOI
Variable precision rough set model
TL;DR: 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.
Book ChapterDOI
The Discernibility Matrices and Functions in Information Systems
Andrzej Skowron,Cecylia Rauszer +1 more
TL;DR: In this article, the authors introduce two notions related to any information system, namely the discernibility matrix and discernibility function, and obtain several algorithms for solving problems related among other things to the rough definability, reducts, core and dependencies generation.