Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
Rough set algorithms in classification problem
Rough set methods and applications
Semantics-Preserving Dimensionality Reduction: Rough and Fuzzy-Rough-Based Approaches
IEEE Transactions on Knowledge and Data Engineering
Particle Swarm Algorithm for Minimal Attribute Reduction of Decision Data Tables
IMSCCS '06 Proceedings of the First International Multi-Symposiums on Computer and Computational Sciences - Volume 2 (IMSCCS'06) - Volume 02
Feature selection based on rough sets and particle swarm optimization
Pattern Recognition Letters
An efficient ant colony optimization approach to attribute reduction in rough set theory
Pattern Recognition Letters
Attribute reduction in decision-theoretic rough set models
Information Sciences: an International Journal
Attribute selection with fuzzy decision reducts
Information Sciences: an International Journal
Three-way decisions with probabilistic rough sets
Information Sciences: an International Journal
New approaches to fuzzy-rough feature selection
IEEE Transactions on Fuzzy Systems
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Positive approximation: An accelerator for attribute reduction in rough set theory
Artificial Intelligence
A new fitness function for solving minimum attribute reduction problem
RSKT'10 Proceedings of the 5th international conference on Rough set and knowledge technology
An Attribute Reduction Algorithm Based on Clustering and Attribute-Activity Sorting
ICCIS '10 Proceedings of the 2010 International Conference on Computational and Information Sciences
Solving the attribute reduction problem with ant colony optimization
Transactions on rough sets XIII
Information Sciences: an International Journal
Analysis of alternative objective functions for attribute reduction in complete decision tables
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special issue on advances in computational intelligence and bioinformatics
Finding minimal rough set reducts with particle swarm optimization
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part I
Parameterized attribute reduction with Gaussian kernel based fuzzy rough sets
Information Sciences: an International Journal
Rough set approach to incomplete numerical data
Information Sciences: an International Journal
Quick attribute reduction in inconsistent decision tables
Information Sciences: an International Journal
A novel method for attribute reduction of covering decision systems
Information Sciences: an International Journal
Hi-index | 0.07 |
The minimum attribute reduction (MAR) problem in the context of rough set theory is known to be NP-hard. One popular way of dealing with this problem is to first transform it into a fitness maximization problem over a multi-dimensional Boolean space, and to then solve this problem using population-based stochastic optimization algorithms. It is therefore important to have an appropriate fitness function. In this paper, two examples are presented to show that existing fitness functions either do not guarantee optimality equivalence between the MAR problem and the transformed fitness maximization problem, or may produce the so-called overemphasis phenomenon that affects the performance of population-based stochastic optimization algorithms. To overcome these drawbacks, we propose a new fitness function that we prove both guarantees the optimality equivalence and reduces the overemphasis phenomenon. Experimental results show that the proposed fitness function is better than existing fitness functions in terms of solution quality.