I have a data mining assignment where I make a content-based image retrieval system. I have 20 images of 5 animals. So in total 100 images.

My code returns the 10 most relevant images to an input image.

Now I need to evaluate the performance of my system with a Precision-Recall curve. However, I do not understand the concept of a Precision-Recall curve.

Let's say my system returns 10 most relevant images of a gorilla, but only 4 of them are gorillas. The other 6 images returned are other animals'.

Now my precision is 4/10 = 0.4 and my recall is 4/20 = 0.2

So I only have a point <0.2,0.4> not a curve.

How do I have a curve?

By changing the number of images returned (which is fixed = 10 in my case) ?

Any help would be appreciated,

Thanks !


closed as off-topic by Geoff Oxberry Apr 18 '14 at 21:32

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  • $\begingroup$ Please don't post identical questions on multiple StackExchange sites. This is a dupe of stats.stackexchange.com/questions/94189/… $\endgroup$ – Marc Claesen Apr 18 '14 at 21:06
  • $\begingroup$ This question is not really off-topic. It is a cross-post, and cross-posting is discouraged. $\endgroup$ – Geoff Oxberry Apr 18 '14 at 21:32
  • $\begingroup$ @GeoffOxberry if the question is not really off-topic, why did you close it with reason "off-topic"? $\endgroup$ – Federico Poloni Apr 20 '14 at 17:06
  • $\begingroup$ @FedericoPoloni: We close cross-posted questions as a matter of policy. "Off-topic" is one of the more flexible reasons; it allows a person to enter a custom reason for closure, which is converted to a comment. The "duplicate" reason for closing will not work because it requires that the duplicate question also be on SciComp; for cross-posts, that condition is never satisfied by definition. $\endgroup$ – Geoff Oxberry Apr 20 '14 at 20:30
  • $\begingroup$ @GeoffOxberry I see, thanks for the explanation. So it seems to be an interface issue in Stack Exchange. $\endgroup$ – Federico Poloni Apr 20 '14 at 21:28

Please check this link: http://en.wikipedia.org/wiki/Precision_and_recall

Check the ROC section as well. This is a very clear description I think. For a more thorough understanding, I would recommend:


  • $\begingroup$ Thanks! The wikipedia article didn't help. I will try to read the paper. $\endgroup$ – jeff Apr 18 '14 at 18:15

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