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AUSAI
2009
Springer
14 years 2 months ago
Ensemble Approach for the Classification of Imbalanced Data
Ensembles are often capable of greater prediction accuracy than any of their individual members. As a consequence of the diversity between individual base-learners, an ensemble wil...
Vladimir Nikulin, Geoffrey J. McLachlan, Shu-Kay N...
ICML
2007
IEEE
14 years 11 months ago
Learning a meta-level prior for feature relevance from multiple related tasks
In many prediction tasks, selecting relevant features is essential for achieving good generalization performance. Most feature selection algorithms consider all features to be a p...
Su-In Lee, Vassil Chatalbashev, David Vickrey, Dap...
ILP
2003
Springer
14 years 3 months ago
A Comparative Evaluation of Feature Set Evolution Strategies for Multirelational Boosting
Boosting has established itself as a successful technique for decreasing the generalization error of classification learners by basing predictions on ensembles of hypotheses. Whil...
Susanne Hoche, Stefan Wrobel
WEBI
2010
Springer
13 years 8 months ago
How to Improve Your Google Ranking: Myths and Reality
Abstract--Search engines have greatly influenced the way people access information on the Internet as such engines provide the preferred entry point to billions of pages on the Web...
Ao-Jan Su, Y. Charlie Hu, Aleksandar Kuzmanovic, C...
MCS
2009
Springer
14 years 4 months ago
Ensemble Strategies for Classifying Hyperspectral Remote Sensing Data
The classification of hyperspectral imagery, using multiple classifier systems is discussed and an SVM-based ensemble is introduced. The data set is separated into separate featu...
Xavier Ceamanos, Björn Waske, Jon Atli Benedi...