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MCS
2005
Springer
14 years 1 months ago
Ensemble of SVMs for Incremental Learning
Support Vector Machines (SVMs) have been successfully applied to solve a large number of classification and regression problems. However, SVMs suffer from the catastrophic forgetti...
Zeki Erdem, Robi Polikar, Fikret S. Gürgen, N...
TCBB
2011
13 years 2 months ago
Ensemble Learning with Active Example Selection for Imbalanced Biomedical Data Classification
—In biomedical data, the imbalanced data problem occurs frequently and causes poor prediction performance for minority classes. It is because the trained classifiers are mostly d...
Sangyoon Oh, Min Su Lee, Byoung-Tak Zhang
AI
2002
Springer
13 years 7 months ago
Ensembling neural networks: Many could be better than all
Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the relationship between the ensemble and its compone...
Zhi-Hua Zhou, Jianxin Wu, Wei Tang
MCS
2007
Springer
14 years 1 months ago
Stopping Criteria for Ensemble-Based Feature Selection
Selecting the optimal number of features in a classifier ensemble normally requires a validation set or cross-validation techniques. In this paper, feature ranking is combined with...
Terry Windeatt, Matthew Prior
WWW
2007
ACM
14 years 8 months ago
Page-level template detection via isotonic smoothing
We develop a novel framework for the page-level template detection problem. Our framework is built on two main ideas. The first is the automatic generation of training data for a ...
Deepayan Chakrabarti, Ravi Kumar, Kunal Punera