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allow loss metric to be configurable by the user #67

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jolars opened this issue Apr 3, 2020 · 1 comment
Open

allow loss metric to be configurable by the user #67

jolars opened this issue Apr 3, 2020 · 1 comment

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@jolars
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jolars commented Apr 3, 2020

Possible loss metrics include:

  • \sum{i=1}{n} ( (A_i - \omega_i)(A_i )^2 (for A_i != 0).

please comment if there are any other loss metrics that you would want to include

@gwselke
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gwselke commented Apr 3, 2020

For me, choice between absolute errors (implemented now) and relative errors (described above) seems enough to cover a wide range of scenarios. One could consider other norms than euclidean, but that would rather seem to be a technical variation without much added practical value. Well, maybe max norm (\max(...) instead of \sum((...)^2).

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