Sciweavers

1863 search results - page 203 / 373
» A supervised learning approach for imbalanced data sets
Sort
View
ICPR
2010
IEEE
15 years 6 months ago
Adaptive Incremental Learning with an Ensemble of Support Vector Machines
The incremental updating of classifiers implies that their internal parameter values can vary according to incoming data. As a result, in order to achieve high performance, incre...
Marcelo N. Kapp, Robert Sabourin, Patrick Maupin
ICML
2007
IEEE
16 years 7 months ago
Maximum margin clustering made practical
Maximum margin clustering (MMC) is a recent large margin unsupervised learning approach that has often outperformed conventional clustering methods. Computationally, it involves n...
Kai Zhang, Ivor W. Tsang, James T. Kwok
SDM
2008
SIAM
130views Data Mining» more  SDM 2008»
15 years 8 months ago
Mining Sequence Classifiers for Early Prediction
Supervised learning on sequence data, also known as sequence classification, has been well recognized as an important data mining task with many significant applications. Since te...
Zhengzheng Xing, Jian Pei, Guozhu Dong, Philip S. ...
IROS
2009
IEEE
146views Robotics» more  IROS 2009»
16 years 1 months ago
Robust constraint-consistent learning
— Many everyday human skills can be framed in terms of performing some task subject to constraints imposed by the environment. Constraints are usually unobservable and frequently...
Matthew Howard, Stefan Klanke, Michael Gienger, Ch...
IJAR
2010
130views more  IJAR 2010»
15 years 5 months ago
Learning locally minimax optimal Bayesian networks
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Tomi Silander, Teemu Roos, Petri Myllymäki