A Simple and Effective Lagrangian-Based Combinatorial Algorithm for S~3VMs

摘要

Many optimization techniques have been developed in the last decade to include the unlabeled patterns in the Support Vector Machines formulation. Two broad strategies are followed: continuous and combinatorial. The approach presented in this paper belongs to the latter family and is especially suitable when a fair estimation of the proportion of positive and negative samples is available. Our method is very simple and requires a very light parameter selection. Experiments on both artificial and real-world datasets have been carried out, proving the effectiveness and the efficiency of the proposed algorithm.