Abstract
Classification of leukemia samples based on gene expression profiles has been proved an efficient way. Large numbers of intelligence algorithms have been exploited based on this purpose. However, few of them display stable and accurate performance for both low and high gene dimensionalities. Still none of them could keep the history information of optimization. Here, a classification algorithm based on the novel multivariant optimization algorithm (MOA) is proposed. Leukemia gene expression profiles with different dimensionalities are used for validation. The particle swarm optimization (PSO) and the two-layer particle swarm optimization (TLPSO) algorithm are used for comparison. The MOA shows stable and relatively accurate classification performance and could be used as an effective classification algorithm for gene expression profiles.
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