Before revision:  Using four synthetic datasets of complex systems--three biological models and one network flow optimization model--we demonstrate that when the number of training samples is small compared to the number of features, the simulation kernel approach dominates over no-prior-knowledge methods.
After revision:  Using four synthetic datasets of complex systems--three biological models and one network flow optimization model. We show that, when the number of training samples is small compared to the number of features, the simulation kernel approach dominates over no-prior-knowledge methods.