Reputation: 839
I have a face detection system with SVM as the classifier. The classifier outputs a confidence level, between 0 and 1 , along with the decision. As in any detection system, there are several false positives too. To eliminate some of them, we can use non-maxima suppression (Please see http://www.di.ens.fr/willow/teaching/recvis10/assignment4/). The confidence threshold for detection is set manually. For example any detection with confidence below 0.6 is a false positive. Is there a way to set this threshold automatically ?
For example using something in detection/ estimation theory?
Upvotes: 2
Views: 5450
Reputation: 6544
If you search for probability calibration you will find some research on a related matter (recalibrating the outputs to return better scores).
If your problem is a binary classification problem, you can calculate the slope of the cost by assigning vales to true/false positive/negative options multiplied by the class ratio. You can then form a line with the given AUC curve that intersects at only one point to find a point that is in some sense optimal as a threshold for your problem.
Upvotes: 1