Proving that a Hypothesis Class is not PAC-Learnable

I was wondering how one can show that a class of classifiers $H$ is not PAC-learnable (in the realizable case) without using VC-dimensions in the argument? I know how to show PAC-learnability through the PAC requirements. But what I'm not sure how to show that it's not PAC-learnable. Thanks

Topic pac-learning

Category Data Science

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