Heuristic Attempts to Improve the Generalization Capacities in Learning SVMs
Luminiţa State, Catalina Lucia COCIANU, Marinela Mircea · 2012
The paper reports some new variants of gradient ascent type in learning SVMs. The theoretical development is presented in the third section of the paper. The performance analysis of the proposed variants, in terms of recognition accuracy and generalization capacity, is experimentally evaluated and the results are presented and commented in the final part of the paper.