LEARNING-PATTERN CLASSIFICATION - A SURVEY

Classical and recent results in statistical pattern recognition and le arning theory are reviewed in a two-class pattern classification setti ng, This basic model best illustrates intuition and analysis technique s while still containing the essential features and serving as a proto type for many applications. Topics discussed include nearest neighbor, kernel, and histogram methods, Vapnik-Chervonenkis theory, and neural networks. The presentation and the large (though nonexhaustive) list of references is geared to provide a useful overview of this field for both specialists and nonspecialists.