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» Combining VTS model compensation and support vector machines
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ICML
2003
IEEE
15 years 10 months ago
Hidden Markov Support Vector Machines
This paper presents a novel discriminative learning technique for label sequences based on a combination of the two most successful learning algorithms, Support Vector Machines an...
Yasemin Altun, Ioannis Tsochantaridis, Thomas Hofm...
NPL
2006
98views more  NPL 2006»
14 years 9 months ago
Lamb Meat Quality Assessment by Support Vector Machines
The correct assessment of meat quality (i.e., to fulfill the consumer's needs) is crucial element within the meat industry. Although there are several factors that affect the ...
Paulo Cortez, Manuel Portelinha, Sandra Rodrigues,...
CVBIA
2005
Springer
15 years 3 months ago
Segmenting Brain Tumors with Conditional Random Fields and Support Vector Machines
Abstract. Markov Random Fields (MRFs) are a popular and wellmotivated model for many medical image processing tasks such as segmentation. Discriminative Random Fields (DRFs), a dis...
Chi-Hoon Lee, Mark Schmidt, Albert Murtha, Aalo Bi...
ICML
2004
IEEE
15 years 10 months ago
Robust feature induction for support vector machines
The goal of feature induction is to automatically create nonlinear combinations of existing features as additional input features to improve classification accuracy. Typically, no...
Rong Jin, Huan Liu
ESWA
2007
176views more  ESWA 2007»
14 years 9 months ago
Credit scoring with a data mining approach based on support vector machines
The credit card industry has been growing rapidly recently, and thus huge numbers of consumers’ credit data are collected by the credit department of the bank. The credit scorin...
Cheng-Lung Huang, Mu-Chen Chen, Chieh-Jen Wang