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Erschienen in:
2014 | OriginalPaper | Buchkapitel
A Hybrid Approach for Cancer Classification Based on Particle Swarm Optimization and Prior Information
verfasst von : Fei Han, Ya-Qi Wu, Yu Cui
Erschienen in: Advances in Swarm Intelligence
Verlag: Springer International Publishing
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In this paper, an improved method for cancer classification based on particle swarm optimization (PSO) and priorinformation is proposed. Firstly, the proposed method uses PSO to implement gene selection. Then, the global search algorithm such as PSO is combined with the local search one such as backpropagation (BP) to model the classifier. Moreover, the prior information extracted from the data is encoded in PSO for better performance. The proposed approach is validated on two publicly available microarray data sets. The experimental results verify that the proposed method selects fewer discriminative genes with comparable performance to the traditional classification approaches.