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< mscsirmaster>
hello
< mscsirmaster>
would like to do a few questions, got an algorithm which compare two arrays based on a fixed distance which help us to detect which values are out of range, every failed value is added to a counter, after finish we calculate a percentage of how many data is wrong in an array, since there is two arrays, one is the processed array, and the right is the control array, but we can't find any method to implement this in MLPack
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< zoq>
mscsirmaste: double counter = arma::accu(A - B > max); where A and B is of type arma::vec?
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< davida>
zoq: I was reading your code sample for the new recurrent test. You mentioned that RNN Train() now takes a field, but I see in your example that you are reshaping the inputs and labels to cubes and training one sample at a time rather than using a field as an input. Am I understanding this correctly?
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< zoq>
davida: Right, once the patch is ready the RNN will support arma::filed as input, but internally it's bascially the same.
< davida>
zoq: so for inputs, I need to setup a field containing 'm' cubes where each cube represents 1 sample? Meaning the 'k' order of the cube should always be 1?
< davida>
Sorry - the 'j' dimension (assuming cube(i,j,k)