Comparison of L1 and L2 support vector machines

摘要

In this paper, we compare L1 and L2 support vector machines from the standpoint of training time and the generalization ability. The generalization ability for seven benchmark data sets are almost the same but training time of L1-SVMs is usually shorter than that of L2-SVMs. We also compare the effect of the approximate KKT (Karush-Kuhn-Tucker) conditions using the bias term and the exact KKT conditions. According to the computer experiments, since the approximate KKT conditions give a conservative estimate of violating variables, training time using the approximate KKT conditions is usually shorter.