Say i am training a neural network and have 10 samples with 4 variables each and 1 label assigned to each observation. What does it mean to say that the samples are independent and identically distributed?
I know what IID variables are. And i have read statements such as "Because we usually assume that our samples are independent and identically distributed, the likelihood over all of our examples decomposes into a product over the likelihoods of individual examples: text omitted". What exactly does it mean for the samples (here 4 variables and 1 class label) to be iid?