Can anyone recommend an algorithm/toolkit to rank items that have been rated in a hot-or-not style that gives statistical significance?
For example, out of a set of N images, two images are shown to users and the user picks the one that appeals most to him/her. The final output is a ranking: worst to best: image1 image5 image3 image8 etc.
I've come across the Bradley-Terry model with maximum-likelihood inference but I haven't found a toolkit that shows statistical significance of the rating.
Any toolkits in python especially would be much appreciated (though R is fine too).