DOC: Clarify how candidate split thresholds are chosen in DecisionTre… #32173
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cakedev0
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Sep 12, 2025
doc/modules/ensemble.rst
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| distinct feature values. This results in up to ``O(N × F)`` candidate | ||
| thresholds, where ``N`` is the number of samples at the node and ``F`` is |
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Note: not sure how relevant it is for the doc, but for one features, the number of candidate thresholds might be much less than N, it's actually:
- number of unique values in X[:, f] minus one, if there are no missing values
- 2 x n_uniques - 1, if there are missing values (and NaN is not counted in n_uniques)
virchan
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Sep 15, 2025
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Thanks for the PR, @raixyzaditya.
I noticed you already opened #32180 with the same proposed changes, so I'll close this one in favour of that.
Also, just so you know, you don't need to open a new PR each time you want to update your changes. You can simply commit the changes and push them to the same feature branch.
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Closes #27159
Added clarification in documentation explaining how candidate split thresholds
are chosen in DecisionTree and RandomForest. Thresholds are the midpoints between
successive distinct feature values, leading to O(N × F) candidate splits.