Login / Signup
REPMAC: A New Hybrid Approach to Highly Imbalanced Classification Problems.
Hernán Ahumada
Guillermo L. Grinblat
Lucas C. Uzal
Pablo M. Granitto
H. 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