Learning pattern classification-A survey

Sanjeev R. Kulkarni, Gabor Lugosi, Santosh S. Venkatesh

Research output: Contribution to journalArticle

104 Scopus citations

Abstract

Classical and recent results in statistical pattern recognition and learning theory are reviewed in a two-class pattern classification setting. This basic model best illustrates intuition and analysis techniques while still containing the essential features and serving as a prototype for many applications. Topics discussed include nearest neighbor, kernel, and histogram methods, Vapnik-Chervonenkis theory, and neural networks. The presentation and the large (thogh nonexhaustive) list of references is geared to provide a useful overview of this field for both specialists and nonspecialists. Index Terms-Classification, learning, statistical pattern recognition, survey review.

Original languageEnglish (US)
Pages (from-to)2178-2206
Number of pages29
JournalIEEE Transactions on Information Theory
Volume44
Issue number6
DOIs
StatePublished - Dec 1 1998

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences

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