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» Multi-information Ensemble Diversity
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ICPR
2008
IEEE
14 years 9 months ago
The implication of data diversity for a classifier-free ensemble selection in random subspaces
Ensemble of Classifiers (EoC) has been shown effective in improving the performance of single classifiers by combining their outputs. By using diverse data subsets to train classi...
Albert Hung-Ren Ko, Robert Sabourin, Luiz E. Soare...
MDAI
2005
Springer
14 years 1 months ago
Cancer Prediction Using Diversity-Based Ensemble Genetic Programming
Combining a set of classifiers has often been exploited to improve the classification performance. Accurate as well as diverse base classifiers are prerequisite to construct a good...
Jin-Hyuk Hong, Sung-Bae Cho
CIDM
2009
IEEE
14 years 3 months ago
Diversity analysis on imbalanced data sets by using ensemble models
— Many real-world applications have problems when learning from imbalanced data sets, such as medical diagnosis, fraud detection, and text classification. Very few minority clas...
Shuo Wang, Xin Yao
SIGIR
2006
ACM
14 years 2 months ago
Feature diversity in cluster ensembles for robust document clustering
The performance of document clustering systems depends on employing optimal text representations, which are not only difficult to determine beforehand, but also may vary from one ...
Xavier Sevillano, Germán Cobo, Francesc Al&...
SBRN
2006
IEEE
14 years 2 months ago
A Dynamic Classifier Selection Method to Build Ensembles using Accuracy and Diversity
Alixandre Santana, Rodrigo G. F. Soares, Anne M. P...