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JMLR
2006
105views more  JMLR 2006»
13 years 8 months ago
Some Theory for Generalized Boosting Algorithms
We give a review of various aspects of boosting, clarifying the issues through a few simple results, and relate our work and that of others to the minimax paradigm of statistics. ...
Peter J. Bickel, Yaacov Ritov, Alon Zakai
ICML
1999
IEEE
14 years 9 months ago
AdaCost: Misclassification Cost-Sensitive Boosting
AdaCost, a variant of AdaBoost, is a misclassification cost-sensitive boosting method. It uses the cost of misclassifications to update the training distribution on successive boo...
Wei Fan, Salvatore J. Stolfo, Junxin Zhang, Philip...
MCS
2007
Springer
14 years 2 months ago
Random Feature Subset Selection for Ensemble Based Classification of Data with Missing Features
Abstract. We report on our recent progress in developing an ensemble of classifiers based algorithm for addressing the missing feature problem. Inspired in part by the random subsp...
Joseph DePasquale, Robi Polikar
IPPS
2002
IEEE
14 years 1 months ago
Concept-Based Component Libraries and Optimizing Compilers
This paper discusses concept lattices and some of their applications in component library development and compiler optimizations. Ongoing work on concept-based userextensible simp...
Sibylle Schupp, D. P. Gregor, B. Osman, David R. M...
NIPS
2003
13 years 10 months ago
On the Dynamics of Boosting
In order to understand AdaBoost’s dynamics, especially its ability to maximize margins, we derive an associated simplified nonlinear iterated map and analyze its behavior in lo...
Cynthia Rudin, Ingrid Daubechies, Robert E. Schapi...