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» Support Vector Machines: Theory and Applications
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KDD
2010
ACM
175views Data Mining» more  KDD 2010»
13 years 11 months ago
Learning with cost intervals
Existing cost-sensitive learning methods work with unequal misclassification cost that is given by domain knowledge and appears as precise values. In many real-world applications,...
Xu-Ying Liu, Zhi-Hua Zhou
ICDM
2007
IEEE
248views Data Mining» more  ICDM 2007»
13 years 11 months ago
Adapting SVM Classifiers to Data with Shifted Distributions
Many data mining applications can benefit from adapting existing classifiers to new data with shifted distributions. In this paper, we present Adaptive Support Vector Machine (Ada...
Jun Yang 0003, Rong Yan, Alexander G. Hauptmann
AIRS
2006
Springer
13 years 11 months ago
A Semantic Fusion Approach Between Medical Images and Reports Using UMLS
One of the main challenges in content-based image retrieval still remains to bridge the gap between low-level features and semantic information. In this paper, we present our first...
Daniel Racoceanu, Caroline Lacoste, Roxana Teodore...
FSKD
2006
Springer
124views Fuzzy Logic» more  FSKD 2006»
13 years 11 months ago
An Effective Combination of Multiple Classifiers for Toxicity Prediction
This paper presents an investigation into the combination of different classifiers for toxicity prediction. These classification methods involved in generating classifiers for comb...
Gongde Guo, Daniel Neagu, Xuming Huang, Yaxin Bi
AVBPA
2003
Springer
133views Biometrics» more  AVBPA 2003»
13 years 11 months ago
LUT-Based Adaboost for Gender Classification
There are two main approaches to the problem of gender classification, Support Vector Machines (SVMs) and Adaboost learning methods, of which SVMs are better in correct rate but ar...
Bo Wu, Haizhou Ai, Chang Huang