UCL logo

UCL Discovery

UCL home » Library Services » Electronic resources » UCL Discovery

Balanced sensitivity and specificity on unbalanced data using support vector machine re-thresholding

Ridgway, GR; Lehmann, M; Rohrer, J; Clarkson, M; Warren, J; Ourselin, S; Fox, N; (2011) Balanced sensitivity and specificity on unbalanced data using support vector machine re-thresholding. Presented at: AAICAD Alzheimer's Imaging Consortium, Paris, France. Green open access

[img]
Preview
PDF
Ridgway2011_ICAD_SVM.pdf
Available under License : See the attached licence file.

Download (811kB)

Abstract

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.

Type: Poster
Title: Balanced sensitivity and specificity on unbalanced data using support vector machine re-thresholding
Event: AAICAD Alzheimer's Imaging Consortium
Location: Paris, France
Open access status: An open access version is available from UCL Discovery
Publisher version: http://www.alz.org/aaic/consortium.asp
Language: English
Keywords: SVM, MVPA, Classifier, Classification
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Neurodegenerative Diseases
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
URI: http://discovery.ucl.ac.uk/id/eprint/1316158
Downloads since deposit
402Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item