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Detection of breast cancer using an asymmetric entropy measure

Published inCOMPSTAT 2006 - Proceedings in Computational Statistics, Editors Rizzi, Alfredo and Vichi, Maurizio, p. 975-982
Presented at Berlin, 2006
Publication date2006
Abstract

In this paper we present a new entropy measure to grow decision trees. This measure has the characteristic to be asymmetric, allowing the user to grow trees which better correspond to his expectation in terms of recall and precision on each class. Then we propose decision rules adapted to such trees. Experiments have been realized on real medical data from breast cancer screening units.

Keywords
  • Entropy measures
  • Decision trees
  • Classification
  • Asymmetric error
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Citation (ISO format)
MARCELLIN, Simon, ZIGHED, Djamel A., RITSCHARD, Gilbert. Detection of breast cancer using an asymmetric entropy measure. In: COMPSTAT 2006 - Proceedings in Computational Statistics. Berlin. [s.l.] : [s.n.], 2006. p. 975–982.
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