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The ROC-boost design algorithm for asymmetric classification

  • Author(s): Cesare, G;
  • Manduchi, R
  • Editor(s): Chen, Xue-wen;
  • Dillon, Tharam S;
  • Ishibuchi, Hisao;
  • Pei, Jian;
  • Wang, Haixun;
  • Wani, M Arif
  • et al.
Abstract

In many situations (e.g., cascaded classification), it is desirable to design a classifier with precise constraints on its detection rate or on its false positive rate. We introduce ROC Boost, a modification of the Ada Boost design algorithm that produces asymmetric classifiers with guaranteed detection rate and low false positive rates. Tested in a visual text detection task, ROC-Boost was shown to perform competitively against other popular algorithms. © 2011 IEEE.

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