Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Journal of Global Optimization
Rough sets and intelligent data analysis
Information Sciences—Informatics and Computer Science: An International Journal
Rough set methods in feature selection and recognition
Pattern Recognition Letters - Special issue: Rough sets, pattern recognition and data mining
A New Rough Set Reduct Algorithm Based on Particle Swarm Optimization
IWINAC '07 Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks
Information Sciences: an International Journal
Mechanical Design Optimization Using Advanced Optimization Techniques
Mechanical Design Optimization Using Advanced Optimization Techniques
Engineering Applications of Artificial Intelligence
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Feature selection is a valuable technique in data analysis for information preserving data reduction. This paper proposes to consider an information system without any decision attribute. The proposal is useful when we get unlabeled data, which contains only input information condition attributes but without decision class attribute. TLBO clustering algorithm is applied to cluster the given information. Decision table could be formulated using this clustered data as the decision variable. Then rough set and TLBO algorithms are applied for selecting features. The experiments are carried out on datasets of UCI machine repository and from the website http://www.ailab.si/orange/datasets.asp to analyse the performance study of our proposed approach with other approaches like genetic algorithm, particle swarm optimisation and differential evolution techniques. The results clearly reveal that our proposed approach outperforms other approaches investigated in this paper.