title: How to rank images based on pairs of comparisons with SVM?
body: <p>I'm working on a neural network to predict scores on how &quot;good&quot; the images are. The images are the inputs to another machine learning algorithm, and the app needs to tell the user how good the image they are taking is for that algorithm.</p>
  <p>I have a training dataset, and I need to rank these images so I can have a score for each one for the regression neural network to train.</p>
  <p>I created a program that gives me 2 images from the training set at a time and I will decide which one wins (or ties). I heard that the full rank can be obtained from these comparisons using <strong>SVM Ranking</strong>. However, I haven't really worked with SVMs before. I only know the very basics of SVMs. I read a few articles on SVM Ranking and it seems like the algorithm turns the ranking problem to a classification problem, but the maths really confuses me.</p>
  <p>Can anyone explain how it works in simple terms and how to implement it in Python?</p>