Neural network input ordering, does it matter?

Question

I have seen similar questions, but most involve preprocessing. Do the order in which the input are ordered have any importance. For example, say I have three features with three examples each such as:

[0, 0, 0, .5, .5, .5, 1, 1, 1]

Would it make any difference if they were ordered like this:

[0, .5, 1, 0, .5, 1, 0, .5, 1]

i.e does the order of the inputs have any effect at all?

Thanks

Answer 1

First your input should be 2D: (n_examples, n_feat) so in your case:

[[0,.5,1],[0,.5,1],[0,.5,1]]

then the ordering of features does not matter as long as it is consistent through the whole training, classification process. So you could as well use:

[[.5,1,0],[.5,1,0],[.5,1,0]]

as long as you keep putting the first feature last everywhere else.