Using the same setting, the system achieves the performance of 91.02% in Accuracy in the same test set.
the main reason is that the tree kernel can capture effectively more structure features while the standard flat features can cover some other useful features, such as Voice, SubCat, which are hard to be covered by the tree kernel.