After we rank all the predictions from a model, we calculate AP_r from 0 to 1.0. Say, we make a limited amount of predictions but we locate all the ground truth provided by the labels. Then we should not have trouble calculating.

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If we cannot locate all the ground truth, some of the p(r) with r close to 1.0 can be considered as 0. Even if we make an “unlimited” number of predictions, those p(r) will approach zero and treated that way also.

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Deep Learning

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