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[ML] Sanity checks for properties of trained boosted trees #2409

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@valeriy42

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@valeriy42
  • Check if the tree consists of a single stub. Produce a warning if this is true.
  • Check that tree doesn't predict NAN. Report an error if a NAN is detected.
  • Check if a recall is 0 on one of the classes. Report a warning if this is true.

Implementation considerations:

  • This sanity check can be applied after predict() is called.
  • The sanity checkers are specific to the used loss function. Hence, they can be acquired from the CLossimplementations.
  • Instead of checks for recall, regression losses may have a stub method.

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