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REPMAC: A New Hybrid Approach to Highly Imbalanced Classification Problems.

Hernán AhumadaGuillermo L. GrinblatLucas C. UzalPablo M. GranittoH. Alejandro Ceccatto
Published in: HIS (2008)
Keyphrases
  • highly imbalanced
  • class distribution
  • data sets
  • imbalanced data
  • cost sensitive
  • training data
  • training samples
  • class imbalance
  • feature selection
  • test set
  • base classifiers
  • decision boundary