Oversampling techniques for a class with 1 sample

I have 5 classes, one of them having only one sample.

I've been researching techniques to oversample such as SMOTE and Bootstrapping but they do not work for the class with only one sample.

I am considering repetition of this class. Are there any other strategies you would recommend?

Would repetition followed by SMOTE make sense or not really? Due to the nature of SMOTE using k-nearest neighbors?

Topic oversampling bootstraping smote

Category Data Science

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