Fuzzy Sets and Systems
Fuzzy Sets and Systems
Fuzzy Sets and Systems
Fuzzy rough sets: application to feature selection
Fuzzy Sets and Systems
Approximation of fuzzy concepts in decision making
Fuzzy Sets and Systems
Axiomatics for fuzzy rough sets
Fuzzy Sets and Systems
Learning optimization in simplifying fuzzy rules
Fuzzy Sets and Systems
A comparative study of fuzzy rough sets
Fuzzy Sets and Systems
An axiomatic characterization of a fuzzy generalization of rough sets
Information Sciences—Informatics and Computer Science: An International Journal
Constructive and axiomatic approaches of fuzzy approximation operators
Information Sciences—Informatics and Computer Science: An International Journal - Mining stream data
On fuzzy-rough sets approach to feature selection
Pattern Recognition Letters
Information-preserving hybrid data reduction based on fuzzy-rough techniques
Pattern Recognition Letters
Fuzzy rough sets hybrid scheme for breast cancer detection
Image and Vision Computing
Fuzzy equivalence relations and their equivalence classes
Fuzzy Sets and Systems
Fuzzy-rough nearest neighbor algorithms in classification
Fuzzy Sets and Systems
FRCT: fuzzy-rough classification trees
Pattern Analysis & Applications
The model of fuzzy variable precision rough sets
IEEE Transactions on Fuzzy Systems
New approaches to fuzzy-rough feature selection
IEEE Transactions on Fuzzy Systems
FRSVMs: Fuzzy rough set based support vector machines
Fuzzy Sets and Systems
Fuzzy-rough data reduction with ant colony optimization
Fuzzy Sets and Systems
A Distance Measure Approach to Exploring the Rough Set Boundary Region for Attribute Reduction
IEEE Transactions on Knowledge and Data Engineering
Gaussian kernel based fuzzy rough sets: Model, uncertainty measures and applications
International Journal of Approximate Reasoning
Building a Rule-Based Classifier—A Fuzzy-Rough Set Approach
IEEE Transactions on Knowledge and Data Engineering
Fuzzy preference based rough sets
Information Sciences: an International Journal
Local reduction of decision system with fuzzy rough sets
Fuzzy Sets and Systems
Soft fuzzy rough sets for robust feature evaluation and selection
Information Sciences: an International Journal
Attribute reduction based on generalized fuzzy evidence theory in fuzzy decision systems
Fuzzy Sets and Systems
Fuzzy decision tree based on fuzzy-rough technique
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special issue on Recent advances on machine learning and Cybernetics
Robust fuzzy rough classifiers
Fuzzy Sets and Systems
A comparative study on heuristic algorithms for generating fuzzydecision trees
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Improving learning accuracy of fuzzy decision trees by hybrid neural networks
IEEE Transactions on Fuzzy Systems
On the generalization of fuzzy rough sets
IEEE Transactions on Fuzzy Systems
Fuzzy Regression Analysis by Support Vector Learning Approach
IEEE Transactions on Fuzzy Systems
Attributes Reduction Using Fuzzy Rough Sets
IEEE Transactions on Fuzzy Systems
Nearest neighbor pattern classification
IEEE Transactions on Information Theory
Parameterized attribute reduction with Gaussian kernel based fuzzy rough sets
Information Sciences: an International Journal
Maximum Ambiguity-Based Sample Selection in Fuzzy Decision Tree Induction
IEEE Transactions on Knowledge and Data Engineering
Hi-index | 0.00 |
Fuzzy rough attribute reduct has been widely used to remove redundant real-valued attributes without discretizing. By now, there are two existing fuzzy rough attribute reduct methods, one is based on dependency function and another based on discernibility matrix. The former proposed by Shen in 2002 can deal with fuzzy decision table FDT with real-valued condition attributes and fuzzy decision attributes. However, this algorithm is not convergent on many real datasets, and the computational complexity of the algorithm increases exponentially with the number of input variables. The latter proposed by Tsang in 2008 can only deal with fuzzy decision table with real-valued condition attributes and symbol-valued decision attributes. In this paper, we extend the latter method and propose two algorithms for calculating all fuzzy rough attribute reducts to deal with fuzzy decision table with real-valued condition and decision attributes. The first algorthim is designed for computing all fuzzy attribute reducts, yet the computation complexity of this algorithm increases exponentially with the number of attributes. The second one which can find one near-optimal reduct is a heuristic variant of the first algorithm. The experimental results show the proposed method is feasible and effective.