Methods for Automatic Classification in Body Surface Mapping

  • G. Schoffa


Our problem may be stated as follows: a digital computer receives map data for several classes of heart diseases and has to decide for a new case into which class this case should be filed. This is a well-known problem and solved in general for pattern classification: A map is described by a finite number n of variables, called features. A particular map is considered as a point in an n-dimensional pattern space encompassing the region in which patterns can occur. Sets of patterns are classified to pattern classes. Then the problem is to classify a set of unknown maps into one of the known classes.


Decision Boundary Pattern Classification Automatic Classification Pattern Class Intrinsic Dimensionality 


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  1. Kanal, L. N., and Chandrasekaran, B., 1968, On Dimensionality and Sample Size in Statistical Pattern Classification, Proc. NEC Conf., pp. 2–7.Google Scholar
  2. Meisel, W. S., 1972, Computer-oriented Approaches to Pattern Recognition, Acad. Press. N.Y., pp. 12–15.Google Scholar
  3. Postweiler, W., 1979, Diplomarbeit, Universitat Karlsruhe.Google Scholar
  4. Sammon, J. D., Foley, D., and Proctor, A., 1970, Considerations of Dimensionality versus Sample Size, IEEE Symp. Adaptive Processes, Austin, Texas.Google Scholar

Copyright information

© Plenum Press, New York 1982

Authors and Affiliations

  • G. Schoffa
    • 1
  1. 1.Institute of BiophysicsUniversity of KarlsruheKarlsruheGermany

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