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» Applying Support Vector Machines to Imbalanced Datasets
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FSKD
2008
Springer
174views Fuzzy Logic» more  FSKD 2008»
13 years 6 months ago
A Hybrid Re-sampling Method for SVM Learning from Imbalanced Data Sets
Support Vector Machine (SVM) has been widely studied and shown success in many application fields. However, the performance of SVM drops significantly when it is applied to the pr...
Peng Li, Pei-Li Qiao, Yuan-Chao Liu
ICDM
2009
IEEE
200views Data Mining» more  ICDM 2009»
13 years 2 months ago
Improving SVM Classification on Imbalanced Data Sets in Distance Spaces
Abstract--Imbalanced data sets present a particular challenge to the data mining community. Often, it is the rare event that is of interest and the cost of misclassifying the rare ...
Suzan Koknar-Tezel, Longin Jan Latecki
DAS
2008
Springer
13 years 7 months ago
New Oversampling Approaches Based on Polynomial Fitting for Imbalanced Data Sets
In classification tasks, class-modular strategy has been widely used. It has outperformed classical strategy for pattern classification task in many applications [1]. However, in ...
Sami Gazzah, Najoua Essoukri Ben Amara
CVPR
2008
IEEE
14 years 7 months ago
Classification using intersection kernel support vector machines is efficient
Straightforward classification using kernelized SVMs requires evaluating the kernel for a test vector and each of the support vectors. For a class of kernels we show that one can ...
Subhransu Maji, Alexander C. Berg, Jitendra Malik
ICMCS
2007
IEEE
133views Multimedia» more  ICMCS 2007»
13 years 11 months ago
Data Modeling Strategies for Imbalanced Learning in Visual Search
In this paper we examine a novel approach to the difficult problem of querying video databases using visual topics with few examples. Typically with visual topics, the examples a...
Jelena Tesic, Apostol Natsev, Lexing Xie, John R. ...