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If I test an image that has been previously used to train a classification model, is it guaranteed to classify correctly?

My guess is that since the parameters have been trained with other images as well, there is no guarantee of getting a correct classification, just a high probability.

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    $\begingroup$ This is correct, there's no guarantee at all, not even a high probability. As usual It depends on the type of model, the data, the number and distribution of the classes. $\endgroup$
    – Erwan
    Dec 9, 2020 at 20:48
  • $\begingroup$ Thank you @Erwan! Do you mind posting this comment as an answer, so that I can accept? $\endgroup$
    – dev
    Dec 9, 2020 at 21:11
  • $\begingroup$ Ok let's not be lazy :) $\endgroup$
    – Erwan
    Dec 9, 2020 at 22:16

1 Answer 1

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This is correct, there's no guarantee at all, not even a high probability. As usual It depends on the type of model, the data, the number and distribution of the classes.

However there's of course a higher chance that the instance would be correctly classified. That's why one shouldn't use a test set containing training instances to estimate the performance of the model, since there's a high risk the performance would be overestimated (data leakage).

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