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Publication Detail
Balanced sensitivity and specificity on unbalanced data using support vector machine re-thresholding
  • Publication Type:
  • Authors:
    Ridgway GR, Lehmann M, Rohrer J, Clarkson M, Warren J, Ourselin S, Fox N
  • Publication date:
  • Name of conference:
    AAICAD Alzheimer's Imaging Consortium
  • Conference place:
    Paris, France
  • Language:
  • Keywords:
    SVM, MVPA, Classifier, Classification
Support vector machine (SVM) classifiers use multivariate patterns to separate two groups by a hyperplane with maximal margin. This strategy tends to obtain good generalisation accuracy on even very high dimensional applications. However, SVMs are not well suited to unbalanced data with very different numbers of cases in each group. In this work we implement a properly cross-validated method for altering the SVM threshold (also known as the bias or cut-point) to re-balance the sensitivity and specificity.
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Dept of Med Phys & Biomedical Eng
Neurodegenerative Diseases
Dept of Med Phys & Biomedical Eng
Neurodegenerative Diseases
Neurodegenerative Diseases
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