  Intuitively, viewing the learner as employing more stochastic and  probabilistic inductive techniques enables one to see how the  unlearning problem might have been overblown. What the argument  claims, rightly, is that negative data near enough do not  exist in the pld. However, what learners need in order to  recover from overgeneralizations, is not negative data per  se, but negative evidence, and arguably, the  pld do contain significant amounts of that. For example: