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» Methods for Dynamic Classifier Selection
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ICML
2006
IEEE
14 years 9 months ago
Pruning in ordered bagging ensembles
We present a novel ensemble pruning method based on reordering the classifiers obtained from bagging and then selecting a subset for aggregation. Ordering the classifiers generate...
Alberto Suárez, Gonzalo Martínez-Mu&...
SDM
2008
SIAM
130views Data Mining» more  SDM 2008»
13 years 10 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. ...
WWW
2007
ACM
14 years 9 months ago
Classifying web sites
In this paper, we present a novel method for the classification of Web sites. This method exploits both structure and content of Web sites in order to discern their functionality....
Christoph Lindemann, Lars Littig
AIA
2007
13 years 10 months ago
Incremental classifier based on a local credibility criterion
In this paper we propose the Local Credibility Concept (LCC), a novel technique for incremental classifiers. It measures the classification rate of the classifier’s local mod...
Herward Prehn, Gerald Sommer
ICC
2007
IEEE
141views Communications» more  ICC 2007»
14 years 3 months ago
Accurate Classification of the Internet Traffic Based on the SVM Method
—The need to quickly and accurately classify Internet traffic for security and QoS control has been increasing significantly with the growing Internet traffic and applications ov...
Zhu Li, Ruixi Yuan, Xiaohong Guan