Efficient multiclass ROC approximation by decomposition via confusion matrix perturbation analysis

ROC analysis has become a standard tool in the design and evaluation of 2-class classification problems. It allows for an analysis that incorporates all possible priors, costs, and operating points, which is important in many real problems, where conditions are often nonideal. Extending this to the...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence. - 1979. - 30(2008), 5 vom: 29. Mai, Seite 810-22
1. Verfasser: Landgrebe, Thomas C W (VerfasserIn)
Weitere Verfasser: Duin, Robert P W
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2008
Zugriff auf das übergeordnete Werk:IEEE transactions on pattern analysis and machine intelligence
Schlagworte:Journal Article Research Support, Non-U.S. Gov't
LEADER 01000naa a22002652 4500
001 NLM178516775
003 DE-627
005 20231223152231.0
007 cr uuu---uuuuu
008 231223s2008 xx |||||o 00| ||eng c
024 7 |a 10.1109/TPAMI.2007.70740  |2 doi 
028 5 2 |a pubmed24n0595.xml 
035 |a (DE-627)NLM178516775 
035 |a (NLM)18369251 
040 |a DE-627  |b ger  |c DE-627  |e rakwb 
041 |a eng 
100 1 |a Landgrebe, Thomas C W  |e verfasserin  |4 aut 
245 1 0 |a Efficient multiclass ROC approximation by decomposition via confusion matrix perturbation analysis 
264 1 |c 2008 
336 |a Text  |b txt  |2 rdacontent 
337 |a ƒaComputermedien  |b c  |2 rdamedia 
338 |a ƒa Online-Ressource  |b cr  |2 rdacarrier 
500 |a Date Completed 10.06.2008 
500 |a Date Revised 28.03.2008 
500 |a published: Print 
500 |a Citation Status MEDLINE 
520 |a ROC analysis has become a standard tool in the design and evaluation of 2-class classification problems. It allows for an analysis that incorporates all possible priors, costs, and operating points, which is important in many real problems, where conditions are often nonideal. Extending this to the multiclass case is attractive, conferring the benefits of ROC analysis to a multitude of new problems. Even though ROC analysis does extend theoretically to the multiclass case, the exponential computational complexity as a function of the number of classes is restrictive. In this paper we show that the multiclass ROC can often be simplified considerably because some ROC dimensions are independent of each other. We present an algorithm that analyses interactions between various ROC dimensions, identifying independent classes, and groups of interacting classes, allowing the ROC to be decomposed. The resultant decomposed ROC hypersurface can be interrogated in a similar fashion to the ideal case, allowing for approaches such as cost-sensitive and Neyman-Pearson optimisation, as well as the volume under the ROC. An extensive bouquet of examples and experiments demonstrates the potential of this methodology 
650 4 |a Journal Article 
650 4 |a Research Support, Non-U.S. Gov't 
700 1 |a Duin, Robert P W  |e verfasserin  |4 aut 
773 0 8 |i Enthalten in  |t IEEE transactions on pattern analysis and machine intelligence  |d 1979  |g 30(2008), 5 vom: 29. Mai, Seite 810-22  |w (DE-627)NLM098212257  |x 1939-3539  |7 nnns 
773 1 8 |g volume:30  |g year:2008  |g number:5  |g day:29  |g month:05  |g pages:810-22 
856 4 0 |u http://dx.doi.org/10.1109/TPAMI.2007.70740  |3 Volltext 
912 |a GBV_USEFLAG_A 
912 |a SYSFLAG_A 
912 |a GBV_NLM 
912 |a GBV_ILN_350 
951 |a AR 
952 |d 30  |j 2008  |e 5  |b 29  |c 05  |h 810-22