Fuzzy-rough data reduction with ant colony optimization
Richard Jensen,Qiang Shen +1 more
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TLDR
A new feature selection mechanism based on ant colony optimization is proposed in an attempt to combat the problem of finding optimal feature subsets in the fuzzy-rough data reduction process.About:
This article is published in Fuzzy Sets and Systems.The article was published on 2005-01-01 and is currently open access. It has received 198 citations till now. The article focuses on the topics: Rough set & Feature selection.read more
Citations
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Journal ArticleDOI
Fuzzy-Rough Sets Assisted Attribute Selection
Richard Jensen,Qiang Shen +1 more
TL;DR: This paper investigates a novel approach based on fuzzy-rough sets, fuzzy rough feature selection (FRFS), that addresses problems and retains dataset semantics and is applied to two challenging domains where a feature reducing step is important; namely, web content classification and complex systems monitoring.
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.
Journal ArticleDOI
Power load forecasting using support vector machine and ant colony optimization
TL;DR: A new feature selection mechanism based on ant colony optimization is proposed in an attempt to combat the aforemention difficulties and denotes that the SVM-learning system has advantage when the information preprocessing is based on data mining technology.
Book
Computational Intelligence and Feature Selection: Rough and Fuzzy Approaches
Richard Jensen,Qiang Shen +1 more
TL;DR: Computational Intelligence and Feature Selection provides a high level audience with both the background and fundamental ideas behind feature selection with an emphasis on those techniques based on rough and fuzzy sets, including their hybridizations.
Journal ArticleDOI
Object segmentation using ant colony optimization algorithm and fuzzy entropy
Wenbing Tao,Hai Jin,Liman Liu +2 more
TL;DR: The experiment results show that the implementation of the proposed fuzzy entropy method incorporating with the ACO provides improved search performance and requires significantly reduced computations, making it suitable for real-time vision applications, such as automatic target recognition (ATR).
References
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Book
Fuzzy sets
TL;DR: A separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
Journal ArticleDOI
Ant system: optimization by a colony of cooperating agents
TL;DR: It is shown how the ant system (AS) can be applied to other optimization problems like the asymmetric traveling salesman, the quadratic assignment and the job-shop scheduling, and the salient characteristics-global data structure revision, distributed communication and probabilistic transitions of the AS.
Programs for Machine Learning
Steven L. Salzberg,Alberto Segre +1 more
TL;DR: In his new book, C4.5: Programs for Machine Learning, Quinlan has put together a definitive, much needed description of his complete system, including the latest developments, which will be a welcome addition to the library of many researchers and students.
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Semantics-preserving dimensionality reduction: rough and fuzzy-rough-based approaches
Richard Jensen,Qiang Shen +1 more