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.