科研之友
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摘要
The recently proposed Reinforced Multicategory Support Vector Machine (RMSVM) has been proven to have desirable theoretical properties as well as competitive numerical accuracy for multi-class classification problems. Currently solving the RMSVM is based on a grid search approach for selecting the tuning parameter , which dramatically increases its computational complexity. To overcome this hurdle we develop a new algorithm RMSVMPATH to compute a regularization solution path for RMSVM. We relax the commonly used continuity assumption and propose a new linear programming approach. Numerical simulations and real data analyses demonstrate that the proposed algorithm can yield a valid solution path at a low computational cost.
