Abstract
The classification of microarray data has positive significance for the judgment of cancer and the determination of clinical programs. However, the high dimensionality and small sample characteristics of the microarray data has brought classification a difficult problem. Aiming at the feature selection problem in microarray data classification, a feature selection algorithm based on artificial bee colony algorithm and genetic algorithm is proposed to solve the dimensionality disaster problem in microarray data classification. Finally, the feature subsets obtained by the algorithm are combined with the SVM(Support Vector Machine)classifier to apply to the six published microarray datasets. The experimental results show that the feature subsets obtained based on the proposed scheme can significantly improve the classification performance.
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