How can I convert 1D sparse data into learnable format for machine learning?
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I wanted to do sequence-to-sequence regression where I have sparse 1D arrays as inputs and 1D signals as outputs. I tried a lstm network but the training loss was just fluctuating instead of decreasing. I figured that might be bacause of the sparsity of the data. Is there any way to deal with this problem, like by changing the sparse dataset into some machine learnable format?
Thanks in advance.