zhengruifeng opened a new pull request, #58691:
URL: https://github.com/apache/spark/pull/58691

   ### What changes were proposed in this pull request?
   
   This pull request adds `TreeEnsembleModel.predict` overloads that accept 
tree models directly.
   It reuses the helper for GBT classification, GBT regression, and random 
forest regression
   prediction. Random forest classification keeps its separate 
class-distribution aggregation.
   
   
   ### Why are the changes needed?
   
   The affected models duplicate scalar tree prediction loops. Centralizing 
those loops makes the
   prediction implementations consistent and avoids allocating root-node or 
tree-weight arrays when
   predicting directly from a model.
   
   
   ### Does this PR introduce _any_ user-facing change?
   
   No.
   
   
   ### How was this patch tested?
   
   No new tests were added because this is a behavior-preserving refactor of 
prediction paths already
   covered by the existing GBT and random forest suites.
   
   The patch passed `git diff --check`, changed-file line-length checks, and 
changed-file non-ASCII
   checks. Unit tests were not run locally.
   
   
   ### Was this patch authored or co-authored using generative AI tooling?
   
   Generated-by: OpenAI Codex (GPT-5)
   


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