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A Family-Based Evolutional Approach for Kernel Tree Selection in SVMs
2010
IEICE transactions on information and systems
Finding a kernel mapping function for support vector machines (SVMs) is a key step towards construction of a high-performanced SVM-based classifier. While some recent methods exploited an evolutional approach to construct a suitable multifunction kernel, most of them searched randomly and diversely. In this paper, the concept of a family of identical-structured kernel trees is proposed to enable exploration of structure space using genetic programming whereas to pursue investigation of
doi:10.1587/transinf.e93.d.909
fatcat:sdla7nl7q5f3vp5slhx7rjsbra