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» Ensemble Approach for the Classification of Imbalanced Data
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DAWAK
2008
Springer
15 years 1 months ago
A Parameter-Free Associative Classification Method
In many application domains, classification tasks have to tackle multiclass imbalanced training sets. We have been looking for a CBA approach (Classification Based on Association r...
Loïc Cerf, Dominique Gay, Nazha Selmaoui, Jea...
102
Voted
SDM
2008
SIAM
177views Data Mining» more  SDM 2008»
15 years 1 months ago
Roughly Balanced Bagging for Imbalanced Data
Imbalanced class problems appear in many real applications of classification learning. We propose a novel sampling method to improve bagging for data sets with skewed class distri...
Shohei Hido, Hisashi Kashima
KDD
2003
ACM
148views Data Mining» more  KDD 2003»
16 years 1 days ago
Mining concept-drifting data streams using ensemble classifiers
Recently, mining data streams with concept drifts for actionable insights has become an important and challenging task for a wide range of applications including credit card fraud...
Haixun Wang, Wei Fan, Philip S. Yu, Jiawei Han
86
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GECCO
2006
Springer
180views Optimization» more  GECCO 2006»
15 years 3 months ago
Improving cooperative GP ensemble with clustering and pruning for pattern classification
A boosting algorithm based on cellular genetic programming to build an ensemble of predictors is proposed. The method evolves a population of trees for a fixed number of rounds an...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
KDD
2002
ACM
157views Data Mining» more  KDD 2002»
16 years 1 days ago
Exploiting unlabeled data in ensemble methods
An adaptive semi-supervised ensemble method, ASSEMBLE, is proposed that constructs classification ensembles based on both labeled and unlabeled data. ASSEMBLE alternates between a...
Kristin P. Bennett, Ayhan Demiriz, Richard Maclin