[mlpack-git] [mlpack] [Proposal]Add a function to visualize the results of sparse_autoencoder (#452)

[stereomatchingkiss]

>I think eventually SparseAutoencoder should be refactored to fit inside of

This remind me, there are other types of autoencoder, like transforming autoencoder, tied autoencoder, and maybe there will be more families of autoencoder pop out, and they could be sparse too. Maybe we should factor out the sparse constraint as another policy? That is, provide an Autoencoder class which allowed to add the sparsity as constraint, then this autoencoder will become SparseAutoencoder.

By the way, any interesting to implement those autoencoder?

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