[vlfeat] 17/44: vl_roc.m: improves doc and returns EER threhsold in the info structure vl_pr.m: improves doc

[Dima Kogan]

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dkogan-guest pushed a commit to branch master
in repository vlfeat.

commit a4e96ebe23ce6ab761119aa0fb3bca9aaf1e8b96
Author: Andrea Vedaldi <vedaldi at gmail.com>
Date:   Fri Oct 31 18:10:49 2014 +0000

    vl_roc.m: improves doc and returns EER threhsold in the info structure
    vl_pr.m: improves doc
---
 toolbox/plotop/vl_pr.m  |  2 +-
 toolbox/plotop/vl_roc.m | 10 ++++++++++
 2 files changed, 11 insertions(+), 1 deletion(-)

diff --git a/toolbox/plotop/vl_pr.m b/toolbox/plotop/vl_pr.m
index 87b67ee..376ea3f 100644
--- a/toolbox/plotop/vl_pr.m
+++ b/toolbox/plotop/vl_pr.m
@@ -84,7 +84,7 @@ function [recall, precision, info] = vl_pr(labels, scores, varargin)
 %     NUMNEGATIVES.
 %
 %   Stable:: false
-%     If set to true, RECALL and PRECISION are returned the same order
+%     If set to true, RECALL and PRECISION are returned in the same order
 %     of LABELS and SCORES rather than being sorted by decreasing
 %     score (increasing recall). Samples with -INF scores are assigned
 %     RECALL and PRECISION equal to NaN.
diff --git a/toolbox/plotop/vl_roc.m b/toolbox/plotop/vl_roc.m
index 11dafe7..4f34877 100644
--- a/toolbox/plotop/vl_roc.m
+++ b/toolbox/plotop/vl_roc.m
@@ -42,6 +42,9 @@ function [tpr,tnr,info] = vl_roc(labels, scores, varargin)
 %     The equal error rate is the value of FPR (or FNR) when the ROC
 %     curves intersects the line connecting (0,0) to (1,1).
 %
+%   info.eerThreshold:: EER threshold.
+%     The value of the score for which the EER is attained.
+%
 %   VL_ROC() accepts the following options:
 %
 %   Plot:: []
@@ -70,6 +73,11 @@ function [tpr,tnr,info] = vl_roc(labels, scores, varargin)
 %     a subset of highly-scoring results are recorded for efficiency
 %     reason.
 %
+%   Stable:: false
+%     If set to true, TPR and TNR are returned in the same order
+%     of LABELS and SCORES rather than being sorted by decreasing
+%     score.
+%
 %   About the ROC curve::
 %     Consider a classifier that predicts as positive all samples whose
 %     score is not smaller than a threshold S. The ROC curve represents
@@ -168,12 +176,14 @@ if nargout > 2 || do_plots
   s = max(find(tnr > tpr)) ;
   if s == length(tpr)
     info.eer = NaN ;
+    info.eerThreshold = 0 ;
   else
     if tpr(s) == tpr(s+1)
       info.eer = 1 - tpr(s) ;
     else
       info.eer = 1 - tnr(s) ;
     end
+    info.eerThreshold = scores(perm(s)) ;
   end
 end
 

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