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shaner92 t1_j0amnbc wrote

  1. Has anyone ever seen SMOTE give good results in real world data??
  2. Depends what the 500 features are, you could very well benefit from dimension reduction, or at least pruning some features, if they are not all equally useful. That is a separate topic though
  3. Lot of work to create fake data when he already has that amount

Playing with the loss functions/metrics is probably the best way to go as you ( u/Far-Butterscotch-436 ) pointed out.

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daavidreddit69 t1_j0b5292 wrote

  1. I believe not, it's just a concept to me, but not a solving method in general
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