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Suppose that we have a fingerprint database consisting of 1000 images from 100 persons (10 images per person), and it is required to design a system to identify the person from his fingerprint image. I know that there is a difference between identification and classification, but can we treat the identification problem as a classification problem by setting the number of classes to be equal to the number of persons (100 in this case)? I know that the identification accuracy is the metric used for assessing the performance of identification systems. For the classification problem, other metrics such as precision, recall and F1 score can be used, in addition to accuracy. Can we use these metrics with the identification problem or not? Is the accuracy the only metric that be used with the identification problem?

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    $\begingroup$ You've got four recent questions where you've gotten quite extensive answers – but have not reacted in any way, neither by vote nor by comment, to these answers. I think we'd be less hesitant to spend a lot of time answering your questions if you showed that you've worked with the answers you've gotten. $\endgroup$ Sep 2, 2021 at 22:28
  • $\begingroup$ The website is useful, and I would like to thank all of you for the big effort and fruitful cooperation. $\endgroup$
    – Noha
    Sep 3, 2021 at 3:39
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    $\begingroup$ The appropriate way of doing that is engaging with answers! $\endgroup$ Sep 3, 2021 at 10:51
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    $\begingroup$ I have done the required voting $\endgroup$
    – Noha
    Sep 3, 2021 at 18:56

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