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dc.contributor.authorDavenport, Mark A.
dc.creatorDavenport, Mark A. 2007-10-31T00:41:37Z 2007-10-31T00:41:37Z 2005-12-01 2006-07-27
dc.description Tech Report
dc.description.abstract Standard classification algorithms aim to minimize the probability of making an incorrect classification. In many important applications, however, some kinds of errors are more important than others. In this report we review cost-sensitive extensions of standard support vector machines (SVMs). In particular, we describe cost-sensitive extensions of the C-SVM and the nu-SVM, which we denote the 2C-SVM and 2nu-SVM respectively. The C-SVM and the nu-SVM are known to be closely related, and we prove that the 2C-SVM and 2nu-SVM share a similar relationship. This demonstrates that the 2C-SVM and 2nu-SVM explore the same space of possible classifiers, and gives us a clear understanding of the parameter space for both versions.
dc.language.iso eng
dc.subject.otherImage Processing and Pattern analysis
dc.title The 2nu-SVM: A Cost-Sensitive Extension of the nu-SVM
dc.type Report
dc.citation.bibtexName techreport
dc.citation.journalTitle Rice University ECE Technical Report 2006-07-27
dc.contributor.orgDigital Signal Processing (
dc.citation.issuenumber TREE 0504
dc.type.dcmi Text
dc.type.dcmi Text

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  • DSP Publications [508]
    Publications by Rice Faculty and graduate students in digital signal processing.
  • ECE Publications [1225]
    Publications by Rice University Electrical and Computer Engineering faculty and graduate students

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