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NIPS
2003
13 years 10 months ago
AUC Optimization vs. Error Rate Minimization
The area under an ROC curve (AUC) is a criterion used in many applications to measure the quality of a classification algorithm. However, the objective function optimized in most...
Corinna Cortes, Mehryar Mohri
ICML
2003
IEEE
14 years 9 months ago
Boosting Lazy Decision Trees
This paper explores the problem of how to construct lazy decision tree ensembles. We present and empirically evaluate a relevancebased boosting-style algorithm that builds a lazy ...
Xiaoli Zhang Fern, Carla E. Brodley
EMNLP
2009
13 years 6 months ago
Model Adaptation via Model Interpolation and Boosting for Web Search Ranking
This paper explores two classes of model adaptation methods for Web search ranking: Model Interpolation and error-driven learning approaches based on a boosting algorithm. The res...
Jianfeng Gao, Qiang Wu, Chris Burges, Krysta Marie...
ML
2012
ACM
413views Machine Learning» more  ML 2012»
12 years 4 months ago
Gradient-based boosting for statistical relational learning: The relational dependency network case
Dependency networks approximate a joint probability distribution over multiple random variables as a product of conditional distributions. Relational Dependency Networks (RDNs) are...
Sriraam Natarajan, Tushar Khot, Kristian Kersting,...
TNN
2010
127views Management» more  TNN 2010»
13 years 3 months ago
RAMOBoost: ranked minority oversampling in boosting
In recent years, learning from imbalanced data has attracted growing attention from both academia and industry due to the explosive growth of applications that use and produce imba...
Sheng Chen, Haibo He, Edwardo A. Garcia