Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
Machine Learning
Redundancy based feature selection for microarray data
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient Feature Selection via Analysis of Relevance and Redundancy
The Journal of Machine Learning Research
Markov blanket-embedded genetic algorithm for gene selection
Pattern Recognition
Different metaheuristic strategies to solve the feature selection problem
Pattern Recognition Letters
A wrapper method for feature selection using Support Vector Machines
Information Sciences: an International Journal
AICCSA '08 Proceedings of the 2008 IEEE/ACS International Conference on Computer Systems and Applications
A memetic algorithm for gene selection and molecular classification of cancer
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Music Composition Using Harmony Search Algorithm
Proceedings of the 2007 EvoWorkshops 2007 on EvoCoMnet, EvoFIN, EvoIASP,EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog: Applications of Evolutionary Computing
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
Harmony search algorithm for solving Sudoku
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part I
Harmony Search Algorithms for Structural Design Optimization
Harmony Search Algorithms for Structural Design Optimization
Enhancing the classification accuracy by scatter-search-based ensemble approach
Applied Soft Computing
Pattern Recognition Letters
Dynamic economic load dispatch using hybrid swarm intelligence based harmony search algorithm
Expert Systems with Applications: An International Journal
A two-stage gene selection scheme utilizing MRMR filter and GA wrapper
Knowledge and Information Systems
A hybrid feature selection method for DNA microarray data
Computers in Biology and Medicine
Information Sciences: an International Journal
Performance assessment of foraging algorithms vs. evolutionary algorithms
Information Sciences: an International Journal
A new hybrid ant colony optimization algorithm for feature selection
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
Parameter determination and feature selection for C4.5 algorithm using scatter search approach
Soft Computing - A Fusion of Foundations, Methodologies and Applications
An Intelligent Tuned Harmony Search algorithm for optimisation
Information Sciences: an International Journal
ICIC'11 Proceedings of the 7th international conference on Intelligent Computing: bio-inspired computing and applications
Feature selection using structural similarity
Information Sciences: an International Journal
Wrapper–Filter Feature Selection Algorithm Using a Memetic Framework
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A comparative study of population-based optimization algorithms for turning operations
Information Sciences: an International Journal
Efficient stochastic algorithms for document clustering
Information Sciences: an International Journal
An improved adaptive binary Harmony Search algorithm
Information Sciences: an International Journal
A harmony search algorithm for nurse rostering problems
Information Sciences: an International Journal
Hi-index | 0.07 |
Gene selection, which is a well-known NP-hard problem, is a challenging task that has been the subject of a large amount of research, especially in relation to classification tasks. This problem addresses the identification of the smallest possible set of genes that could achieve good predictive performance. Many gene selection algorithms have been proposed; however, because the search space increases exponentially with the number of genes, finding the best possible approach for a solution that would limit the search space is crucial. Metaheuristic approaches have the ability to discover a promising area without exploring the whole solution space. Hence, we propose a new method that hybridises the Harmony Search Algorithm (HSA) and the Markov Blanket (MB), called HSA-MB, for gene selection in classification problems. In this proposed approach, the HSA (as a wrapper approach) improvises a new harmony that is passed to the MB (treated as a filter approach) for further improvement. The addition and deletion of operators based on gene ranking information is used in the MB algorithm to further improve the harmony and to fine-tune the search space. The HSA-MB algorithm method works especially well on selected genes with higher correlation coefficients based on symmetrical uncertainty. Ten microarray datasets were experimented on, and the results demonstrate that the HSA-MB has a performance that is comparable to state-of-the-art approaches. HSA-MB yields very small sets of genes while preserving the classification accuracy. The results suggest that HSA-MB has a high potential for being an alternative method of gene selection when applied to microarray data and can be of benefit in clinical practice.