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DAM
2008
83views more  DAM 2008»
15 years 20 days ago
Multi-group support vector machines with measurement costs: A biobjective approach
Support Vector Machine has shown to have good performance in many practical classification settings. In this paper we propose, for multi-group classification, a biobjective optimi...
Emilio Carrizosa, Belen Martin-Barragan, Dolores R...
96
Voted
TITB
2008
136views more  TITB 2008»
15 years 14 days ago
Helicobacter Pylori-Related Gastric Histology Classification Using Support-Vector-Machine-Based Feature Selection
Abstract--This study presents a computer-aided diagnosis system using sequential forward floating selection (SFFS) with support vector machine (SVM) to diagnose gastric histology o...
Chun-Rong Huang, Pau-Choo Chung, Bor-Shyang Sheu, ...
114
Voted
ICCS
2007
Springer
15 years 6 months ago
Active Learning with Support Vector Machines for Tornado Prediction
In this paper, active learning with support vector machines (SVMs) is applied to the problem of tornado prediction. This method is used to predict which storm-scale circulations yi...
Theodore B. Trafalis, Indra Adrianto, Michael B. R...
ICPR
2000
IEEE
15 years 5 months ago
Scaling-Up Support Vector Machines Using Boosting Algorithm
In the recent years support vector machines (SVMs) have been successfully applied to solve a large number of classification problems. Training an SVM, usually posed as a quadrati...
Dmitry Pavlov, Jianchang Mao, Byron Dom
113
Voted
ICASSP
2010
IEEE
15 years 23 days ago
Training a support vector machine to classify signals in a real environment given clean training data
When building a classifier from clean training data for a particular test environment, knowledge about the environmental noise and channel should be taken into account. We propos...
Kevin Jamieson, Maya R. Gupta, Eric Swanson, Hyrum...