One of the greatest advantages of this network is that it does not require any iterative training. One
disadvantage of this network is that it has one hidden node for each training instance and thus requires more
computational resources during execution than many other models. In addition, it does not iteratively train
weights on any of the connections, which can make its generalization less flexible.