Question: One might argue that every learning algorithm works with a fixed set of decision rules, that is to say, the set of all rules that

One might argue that every learning algorithm works with a fixed set of decision rules, that is to say, the set of all rules that the particular algorithm might possibly produce over all possible observations. In light of such an argument, is there really anything new to the perspective of working with a fixed collection of decision rules?

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