#StackBounty: #machine-learning #random-variable #dataset #iid #transfer-learning Transfer Learning: data in the source domain and the …

Bounty: 50

In instance-based transfer learning, it is said that data in the source domain and the target domain are required to be independent and identically distributed. When it says that the data "are required to be independent and identically distributed", I’m assuming it’s actually referring to the generative process for the data, since data itself cannot be i.i.d. (that is, i.i.d. is not a property of data – it’s a property of random variables), right? If so, then does this mean that the two generative processes are i.i.d. with respect to each other? I don’t see how it could be interpreted any other way, but I would just like to confirm.


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