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» On learning algorithm selection for classification
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LCN
2006
IEEE
15 years 8 months ago
Training on multiple sub-flows to optimise the use of Machine Learning classifiers in real-world IP networks
Literature on the use of machine learning (ML) algorithms for classifying IP traffic has relied on fullflows or the first few packets of flows. In contrast, many real-world scenar...
Thuy T. T. Nguyen, Grenville J. Armitage
139
Voted
ICMLA
2010
15 years 16 days ago
Classification Models with Global Constraints for Ordinal Data
Ordinal classification is a form of multi-class classification where there is an inherent ordering between the classes, but not a meaningful numeric difference between them. Althou...
Jaime S. Cardoso, Ricardo Sousa
127
Voted
KDD
2001
ACM
216views Data Mining» more  KDD 2001»
16 years 3 months ago
The distributed boosting algorithm
In this paper, we propose a general framework for distributed boosting intended for efficient integrating specialized classifiers learned over very large and distributed homogeneo...
Aleksandar Lazarevic, Zoran Obradovic
166
Voted
EUSFLAT
2009
679views Fuzzy Logic» more  EUSFLAT 2009»
15 years 11 days ago
Combining Wavelets and Computational Intelligence Methods with Applications on Multi-class Classification Datasets
In this paper, we propose a novel algorithm for wavelet feature extraction as input to a supervised Multi-Class Classifier to improve classification performance. In particular, to ...
Carlos Campos Bracho
ICML
2005
IEEE
16 years 3 months ago
The cross entropy method for classification
We consider support vector machines for binary classification. As opposed to most approaches we use the number of support vectors (the "L0 norm") as a regularizing term ...
Shie Mannor, Dori Peleg, Reuven Y. Rubinstein