Topic
Rough set
About: Rough set is a research topic. Over the lifetime, 14683 publications have been published within this topic receiving 256804 citations.
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Papers
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TL;DR: This paper reviews and compares constructive and algebraic approaches in the study of rough set algebras and states axioms that must be satisfied by the operators.
772 citations
TL;DR: The lower and upper approximation of a set, the basic operations of the theory, are intuitively explained and formally defined.
Abstract: This paper gives basic ideas of rough set theory a new approach to data analysis The lower and upper approximation of a set, the basic operations of the theory, are intuitively explained and formally defined Some applications of rough set theory are briefly outlined and some future problems are outlined
754 citations
TL;DR: This article proposes to bring the various neuro-fuzzy models used for rule generation under a unified soft computing framework, and includes both rule extraction and rule refinement in the broader perspective of rule generation.
Abstract: The present article is a novel attempt in providing an exhaustive survey of neuro-fuzzy rule generation algorithms. Rule generation from artificial neural networks is gaining in popularity in recent times due to its capability of providing some insight to the user about the symbolic knowledge embedded within the network. Fuzzy sets are an aid in providing this information in a more human comprehensible or natural form, and can handle uncertainties at various levels. The neuro-fuzzy approach, symbiotically combining the merits of connectionist and fuzzy approaches, constitutes a key component of soft computing at this stage. To date, there has been no detailed and integrated categorization of the various neuro-fuzzy models used for rule generation. We propose to bring these together under a unified soft computing framework. Moreover, we include both rule extraction and rule refinement in the broader perspective of rule generation. Rules learned and generated for fuzzy reasoning and fuzzy control are also considered from this wider viewpoint. Models are grouped on the basis of their level of neuro-fuzzy synthesis. Use of other soft computing tools like genetic algorithms and rough sets are emphasized. Rule generation from fuzzy knowledge-based networks, which initially encode some crude domain knowledge, are found to result in more refined rules. Finally, real-life application to medical diagnosis is provided.
726 citations
TL;DR: It has been proved that the reduct of a covering is the minimal covering that generates theSame covering lower approximation or the same covering upper approximation, so this concept is also a technique to get rid of redundancy in data mining.
699 citations
Book•
01 Mar 1999
TL;DR: This volume provides a collection of twenty articles containing new material and describing the basic concepts and characterizing features of rough set theory and its integration with fuzzy set theory, for developing an efficient soft computing strategy of machine learning.
Abstract: From the Publisher:
This volume provides a collection of twenty articles containing new material and describing the basic concepts and characterizing features of rough set theory and its integration with fuzzy set theory, for developing an efficient soft computing strategy of machine learning. Written by leading experts from all over the world, the contributions demonstrate how rough-fuzzy hybridization can be made in various ways to provide flexible information processing capabilities for handling different real-life, ambiguous decision-making problems. This volume provides a balanced mix of theory and application.
691 citations