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» Ensembles of biased classifiers
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ICML
2004
IEEE
15 years 12 months ago
Learning and evaluating classifiers under sample selection bias
Classifier learning methods commonly assume that the training data consist of randomly drawn examples from the same distribution as the test examples about which the learned model...
Bianca Zadrozny
ECML
2007
Springer
15 years 3 months ago
Ensembles of Multi-Objective Decision Trees
Abstract. Ensemble methods are able to improve the predictive performance of many base classifiers. Up till now, they have been applied to classifiers that predict a single target ...
Dragi Kocev, Celine Vens, Jan Struyf, Saso Dzerosk...
IJCNN
2006
IEEE
15 years 5 months ago
Reducing Uncertainties in Neural Network Jacobians and Improving Accuracy of Neural Network Emulations with NN Ensemble Approach
—A new application of the NN ensemble technique to improve the accuracy and stability of the calculation of NN emulation Jacobians is presented. The term “emulation” is defin...
Vladimir M. Krasnopolsky
KDD
2003
ACM
148views Data Mining» more  KDD 2003»
15 years 11 months 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
ISMIS
2003
Springer
15 years 4 months ago
Evolutionary Computation for Optimal Ensemble Classifier in Lymphoma Cancer Classification
Owing to the development of DNA microarray technologies, it is possible to get thousands of expression levels of genes at once. If we make the effective classification system with ...
Chanho Park, Sung-Bae Cho