The L 1 -regularized logistic regression was comparable to the SVM with linear kernel in this experiment.
the presented model presents the advantage that it can reduce the number of active features (features with non-zero weights assigned); the L 1 regularization can remove 74%, 48%, and 82% of substitution rules in each dataset.