rapidsai / rapidsai/nvforest

[FEA] Support missing_value in nvForest

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feature request
Dominant language
C++
Stars
15
Forks
23
Avg merge
1d 21h
Merged PRs (30d)
28

Description

nvForest assumes missing value is NaN.
XGBoost, LightGBM and Treelite supports other missing values.
Supporting arbitrary missing value is helpful.
https://github.com/rapidsai/cuml/blob/branch-23.12/cpp/src/fil/internal.cuh#L437

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with the referenced cuML cpp/src/fil/internal.cuh location around line 437 and trace how nvForest currently treats missing values during inference. Done means nvForest supports a caller-specified missing value rather than assuming NaN, with the behavior covered by the relevant existing tests.

Written by the indexing model from the issue text.

Assessment

Tech stack
cpp
Domain
machine-learning
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
35/100

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