Classification of Microarray Data Using Evolutionary Hypernetworks with Subspace Fusion

doi:10.3969/j.issn.0372-2112.2016.10.004

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ACTA ELECTRONICA SINICA ›› 2016, Vol. 44 ›› Issue (10) : 2308-2313. DOI: 10.3969/j.issn.0372-2112.2016.10.004

Classification of Microarray Data Using Evolutionary Hypernetworks with Subspace Fusion

WANG Jin, LIU Bin, ZHANG Jun, CHEN Qiao-song, DENG Xin

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Abstract

In order to solve the over-fitting problem of the traditional pattern recognition approaches under the DNA microarray data with small train samples,a subspace fusion-based evolutionary hypernetwork model is proposed in this paper.With the methods of subspace division,hyperedge coverage,and subspace fusion,the proposed scheme reduces the dependence on the initialization,decreases the fitting error of the data space,and enhances the generalization ability of the evolutionary hypernetwork.The experimental results on four DNA microarray datasets show that the proposed model achieves higher classification accuracy and stronger generalization ability than other compared traditional pattern recognition method.

Key words

pattern recognition / microarray data classification / evolutionary hypernetwork / subspace / over-fitting

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WANG Jin, LIU Bin, ZHANG Jun, CHEN Qiao-song, DENG Xin. Classification of Microarray Data Using Evolutionary Hypernetworks with Subspace Fusion[J]. Acta Electronica Sinica, 2016, 44(10): 2308-2313. https://doi.org/10.3969/j.issn.0372-2112.2016.10.004

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Funding

National Natural Science Foundation of China (No.61203308, No.61403054); Science and Technology Research Program of Chongqing Municipal Education Commission (Natural Science) (No.KJ1400436); Chongqing Research Program of Basic and Frontier Technology (No.cstc2014jcyjA40001)