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» Boosting support vector machines for imbalanced data sets
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ICMCS
2007
IEEE
133views Multimedia» more  ICMCS 2007»
14 years 2 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. ...
AIPRF
2008
13 years 10 months ago
Spam Sender Detection with Classification Modeling on Highly Imbalanced Mail Server Behavior Data
Unsolicited commercial or bulk emails or emails containing viruses pose a great threat to the utility of email communications. A recent solution for filtering is reputation systems...
Yuchun Tang, Sven Krasser, Dmitri Alperovitch, Pau...
CORR
2008
Springer
159views Education» more  CORR 2008»
13 years 8 months ago
Face Detection Using Adaboosted SVM-Based Component Classifier
: Boosting is a general method for improving the accuracy of any given learning algorithm. In this paper we employ combination of Adaboost with Support Vector Machine (SVM) as comp...
Seyyed Majid Valiollahzadeh, Abolghasem Sayadiyan,...
IJON
2008
173views more  IJON 2008»
13 years 8 months ago
Support vector machine classification for large data sets via minimum enclosing ball clustering
Support vector machine (SVM) is a powerful technique for data classification. Despite of its good theoretic foundations and high classification accuracy, normal SVM is not suitabl...
Jair Cervantes, Xiaoou Li, Wen Yu, Kang Li
AUSDM
2006
Springer
177views Data Mining» more  AUSDM 2006»
14 years 8 days ago
On The Optimal Working Set Size in Serial and Parallel Support Vector Machine Learning With The Decomposition Algorithm
The support vector machine (SVM) is a wellestablished and accurate supervised learning method for the classification of data in various application fields. The statistical learnin...
Tatjana Eitrich, Bruno Lang