Frequency counts of feature-value pairs in these classifiers are updated independently, and thus a single instance can possibly contribute to the discovery of more than one useful feature-value pair.
some classifiers such as decision trees are not able to take advantage of this redundancy because of their intrinsic nature of recursive data partitioning.