Selection of Most Responsible Genes for Cancer Disease from Large Attributed Dataset Using Hybrid Approach
نویسندگان
چکیده
High dimensionality has been a major problem for gene array-based cancer classification. Feature Selection (FS) is ordinarily used as a useful technique in order to reduce the dimension of the dataset. For that to get advantages from both methods of feature selection, Individual Feature Ranking (IFR) and Feature Subset Selection (FSS) are combined which is a hybrid approach. Information Gain from IFR and Ant Colony Optimization (ACO) from FSS are combined .To maintain the level of exploration and exploitation during search process in ACO, a Fraction method is used which is proposed in this paper. Keywords— Feature Selection, Ant Colony Optimization, Level of exploration and exploitation in ACO
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