These analyses concerned numeric valued features. Average-case analysis of a nearest neighbor algorithm . Nevertheless , like perceptrons, Bayesian classifiers are Selective Bayesian Classifiers 401 typically limited to learning classes that can be separated by a single decision boundary. Another important assumption that the naive Bayesian classifier makes is that, within each class, the probability distributions for attributes are independent of each other. Average-case analysis of a nearest neighbor algorithm .
Winnow method grows only logarithmically with the number of irrelevant features.
However, the theoretical results are less optimistic for induction methods that search a larger space of concept descriptions. However , the theoretical results are less optimistic for induction methods that search a larger space of concept descriptions. Average-case analysis of a nearest neighbor algorithm . No context found. Average-case analysis of a nearest neighbor algorithm .