Discriminant ECOC: A heuristic method for application dependent design of error correcting output codes

Oriol Pujol, Petia Radeva, Jordi Vitrià

Research output: Contribution to journalArticleResearchpeer-review

200 Citations (Scopus)

Abstract

We present a heuristic method for learning error correcting output codes matrices based on a hierarchical partition of the class space that maximizes a discriminative criterion. To achieve this goal, the optimal codeword separation is sacrificed in favor of a maximum class discrimination in the partitions. The creation of the hierarchical partition set is performed using a binary tree. As a result, a compact matrix with high discrimination power is obtained. Our method is validated using the UCI database and applied to a real problem, the classification of traffic sign images. © 2006 IEEE.
Original languageEnglish
Pages (from-to)1007-1012
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Volume28
Issue number6
DOIs
Publication statusPublished - 1 Jun 2006

Keywords

  • Multiclass classification
  • Multiple classifiers
  • Visual object recognition

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