8. A system, comprising: a data store storing images; one or more processors that interact with the data store and execute instructions that cause the one or more processors to perform operations comprising: identifying, from the data store and as positive images, a first set of images that are considered relevant to a first query based, at least in part, on a first selection rate for images in the first set when presented as search results for the first query; identifying, from the data store and as negative images, a second set of images that differ from the first set of images and that are considered relevant to a different query based, at least in part, on a second selection rate for images in the second set when presented as search results for the different query; training an image relevance model for the first query based on feature values of the positive images and feature values of the negative images; generating a score for each of a plurality of images based on feature values of the plurality of images and the image relevance model; receiving a search query; identifying, from the plurality of images, one or more highest scoring images based on the score for each of one or more of the plurality of images; and providing at least a portion of the one or more highest scoring images as results for the search query.
11. The system of claim 8 , wherein the instructions cause the one or more processors to perform operations comprising: determining, based on image feature values of the highest scoring images, that a first image has at least a threshold level of similarity relative to a second image having a higher score than the first image; and assigning the first image to a presentation position in the search results that is lower than a presentation position of at least a third image having a lower score than the first image.