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 system 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 images for a gorilla image, but only 4 of them are gorillas. The other 6 images returned are other animals'. Thus,
- precision is
4/10 = 0.4(relevants returned) / (all returned)
- recall is
4/20 = 0.2(relevants returned) / (all relevants)
So I only have a point,
<0.2,0.4>, not a curve. How do I have a curve (i.e., a set of points)? Should I change the number of images returned (this is fixed at 10 in my case)?