DD_tools: dd_roc

DD_ROC Receiver Operating Characteristic curve 

        E = DD_ROC(A,W)
        E = DD_ROC(A*W)
        E = A*W*DD_ROC

 Find for a (data description) method W the Receiver Operating
 Characteristic curve over dataset A.  The results are returned in a
 structure E, containing two fields. E.err contains the classification
 errors, E.thr contains the trhesholds for the different operating
 points.

 The first column of E.err gives the fraction of target objects
 rejected (false negative fraction, FN), the second column the fraction
 of outlier objects accepted (the false positive fraction, FP). 

 NOTE: people typically use this ROC definition: false positive FP
 (outlier accepted) on the x-axis, and true positive TP (target
 accepted) on the y-axis. You can retrieve that by using:
   NEWE = [E(:,2) 1-E(:,1)]
 I choose to define E consistent, i.e. both numbers indicate
 'errors'. In the routines PLOTROC and DD_AUC the variable E is
 automatically converted to get the 'standard' plots and AUC values.

See also: plotroc dd_auc dd_error simpleroc dd_eer 

@article{Metz1978,
	author = {Metz, C.E.},
	title = {Basic principles of {ROC} analysis},
	journal = {Seminars in Nuclear Medicine},
	year = {1978},
	volume = {VIII},
	number = {4},
	month = {October}
}



Copyright: D.M.J. Tax, D.M.J.Tax@prtools.org
Faculty EWI, Delft University of Technology
P.O. Box 5031, 2600 GA Delft, The Netherlands