[mlpack-git] [mlpack] Create a function to visualize the features learned by sparse autoencoder (#465)

[stereomatchingkiss]

>So I think that each column of the output matrix should correspond to a maximal input

The purpose of this function is visualize the learning results of autoencoder , even it is non-image data, you could use this function to visualize it too(ex : audio data). Extract the maximal inputs into each col is more general, but  I can not imagine what is the used of it, maybe this is a little bit over designed.

>Also, I think that there should be a bool parameter to MaximalInputs() to determine whether or not the output is going to be rescaled (I'd default it to false, because not all applications are image applications).

I agree with you, not all of the applications are image applications, but the purpose of this function is visualize the results learned by autoencoder, so I think it should scale the range by default, because most of the image readers would assume the range of the images lie between [0,255] or [0, 1]

Appreciate your inputs, this kind of conversations and code reviews really help me learn something.

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https://github.com/mlpack/mlpack/pull/465#issuecomment-152437189
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