Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
Rough set algorithms in classification problem
Rough set methods and applications
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Feature Subset Selection Using a Genetic Algorithm
IEEE Intelligent Systems
Using Rough Sets with Heuristics for Feature Selection
RSFDGrC '99 Proceedings of the 7th International Workshop on New Directions in Rough Sets, Data Mining, and Granular-Soft Computing
Feature selection based on rough sets and particle swarm optimization
Pattern Recognition Letters
Two-Step Particle Swarm Optimization to Solve the Feature Selection Problem
ISDA '07 Proceedings of the Seventh International Conference on Intelligent Systems Design and Applications
An efficient ant colony optimization approach to attribute reduction in rough set theory
Pattern Recognition Letters
Tabu search for attribute reduction in rough set theory
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Computational Intelligence and Feature Selection: Rough and Fuzzy Approaches
Computational Intelligence and Feature Selection: Rough and Fuzzy Approaches
Feature Selection Based on Ant Colony Optimization and Rough Set Theory
ISCSCT '08 Proceedings of the 2008 International Symposium on Computer Science and Computational Technology - Volume 01
Scatter Search for Rough Set Attribute Reduction
CSO '09 Proceedings of the 2009 International Joint Conference on Computational Sciences and Optimization - Volume 01
A rough set approach to feature selection based on ant colony optimization
Pattern Recognition Letters
Feature selection with Intelligent Dynamic Swarm and Rough Set
Expert Systems with Applications: An International Journal
Towards a memetic feature selection paradigm
IEEE Computational Intelligence Magazine
Multi-document summarisation using genetic algorithm-based sentence extraction
International Journal of Computer Applications in Technology
Rough set and scatter search metaheuristic based feature selection for credit scoring
Expert Systems with Applications: An International Journal
Hybrid dynamic k-nearest-neighbour and distance and attribute weighted method for classification
International Journal of Computer Applications in Technology
An Exponential Monte-Carlo algorithm for feature selection problems
Computers and Industrial Engineering
| Hi-index | 0.00 |
Attribute reduction is the problem of selecting a minimal subset from the original set of attributes. Rough set theory has been used for attribute reduction with much success. Since it is well known that finding a minimal subset is a NP-hard problem; therefore, it is necessary to develop efficient algorithms to solve this problem. In this work, we propose a memetic algorithm-based approach inside the rough set theory which is a hybridisation of genetic algorithm and simulated annealing. The proposed method has been tested on UCI data sets. Experimental results demonstrate the effectiveness of this memetic approach when compared with previous available methods. Possible extensions upon this simple approach are also discussed.