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Context: A paper has been conditionally accepted (subject to my major revision). Main issues that have been raised by two reviewers are:

  1. The author should compare the testing times of different algorithms.

  2. Some methods can be added for comparison.

  3. Negative example used in experiment is 50%. According to the size of the dataset, the algorithm may overfit.

  4. The algorithm should be evaluated according to the protocol of a known dataset.

It is clear that the main issues are related to the experiment.

Question: Is it mandatory to conduct new experiments to address issues made by reviewers? If I do not conduct new experiments, what is the probability of getting rejected?

I mean if reviewers are not convinced with experiments, the editor is supposed to reject the paper, but he didn't do that.

What should be done under such circumstances?

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The editor has not rejected because (s)he believes that the shortcomings in your paper can be tackled by you. If this entails performing experiments, then further acceptance will be conditional upon that.

Whether or not you should do these experiments is a different issue and requires knowledge of the case- perhaps you can write a good rebuttal and justify why these added experiments are unnecessary. In general I would recommend against this, but you and your co-authors must make this call based on the issues raised.

Don't think that the editor will necessarily override the reviewers. You need to satisfy the reviewers, either through corrections, rebuttal or a combination of both. Once reviewers are satisfied, editor will be more inclined to accept.

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Ask yourself if these comments are constructive and the added experiments will improve your study design and quality of research. If so, my suggestion is to do the experiments as the reviewers suggested. You may ask the editorial office for longer time of revision if needed. If not, you should state clearly in the response letter why these added experiments are not necessary (beyond the scope of current study, irrelevant to the purpose of your study, etc.) The editor doesn't always override the reviewers. You have to come up with good reasons to convince the reviewers that these experiments are not necessary rather than guessing the probability of getting rejected/accepted.

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