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» Evaluating learning algorithms and classifiers
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ECCV
2010
Springer
15 years 7 months ago
Learning Shape Segmentation Using Constrained Spectral Clustering and Probabilistic Label Transfer
We propose a spectral learning approach to shape segmentation. The method is composed of a constrained spectral clustering algorithm that is used to supervise the segmentation of a...
BMCBI
2010
190views more  BMCBI 2010»
15 years 4 months ago
Sample size and statistical power considerations in high-dimensionality data settings: a comparative study of classification alg
Background: Data generated using `omics' technologies are characterized by high dimensionality, where the number of features measured per subject vastly exceeds the number of...
Yu Guo, Armin Graber, Robert N. McBurney, Raji Bal...
130
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ICML
2010
IEEE
15 years 5 months ago
Risk minimization, probability elicitation, and cost-sensitive SVMs
A new procedure for learning cost-sensitive SVM classifiers is proposed. The SVM hinge loss is extended to the cost sensitive setting, and the cost-sensitive SVM is derived as the...
Hamed Masnadi-Shirazi, Nuno Vasconcelos
ICAPR
2009
Springer
15 years 11 months ago
Relevant and Redundant Feature Analysis with Ensemble Classification
— Feature selection and ensemble classification increase system efficiency and accuracy in machine learning, data mining and biomedical informatics. This research presents an ana...
Rakkrit Duangsoithong, Terry Windeatt
WEA
2010
Springer
311views Algorithms» more  WEA 2010»
15 years 2 months ago
Realtime Classification for Encrypted Traffic
Classifying network flows by their application type is the backbone of many crucial network monitoring and controlling tasks, including billing, quality of service, security and tr...
Roni Bar-Yanai, Michael Langberg, David Peleg, Lia...