A Hybrid Algorithm based on Tabu Search and Chemical Reaction Optimization for Feature Selection of

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  In the last few years,there has been a rapid development in various bioinformatics technologies,which has led to the accumulation of a large amount of biomedical data.The biomedical data can be analyzed to enhance assessment of at-risk patients and improve the diagnosis,treatment and prevention of disease.However,these datasets usually have a large number of features which contains much irrelevant or redundant information.Feature selection is a solution that involves finding the optimal subset,which is known to be an NP problem due to the large search space.
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