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[KNN] Adding default value for oversampling in 9.1.0 #1290

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[KNN] Adding default value for oversampling in 9.1.0 #1290

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865e5ee
adding default value for oversampling in the documentation
Samiul-TheSoccerFan Apr 28, 2025
251291c
updating the documentation for bbq and oversample
Samiul-TheSoccerFan Apr 29, 2025
85feae8
Update documentation wording and adding version
Samiul-TheSoccerFan May 5, 2025
5a34ea3
Merge branch 'main' into update_documentation_for_oversample
Samiul-TheSoccerFan May 6, 2025
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Update documentation wording and adding version
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@Samiul-TheSoccerFan
Samiul-TheSoccerFan committed May 5, 2025
commit 85feae8731e81e47b5ddab252e9950846e2ce7f1
2 changes: 1 addition & 1 deletion solutions/search/vector/knn.md
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Expand Up @@ -901,7 +901,7 @@ Approximate kNN search always uses the [`dfs_query_then_fetch`](https://www.elas

When using [quantized vectors](elasticsearch://reference/elasticsearch/mapping-reference/dense-vector.md#dense-vector-quantization) for kNN search, you can optionally rescore results to balance performance and accuracy, by doing:

* **Oversampling**: Retrieve more candidates per shard. The default is `3.0` in `bbq`.
* **Oversampling**: Retrieve more candidates per shard. Starting in `9.1.0`, the default oversampling factor is 3, but only for the `bbq` quantization method. Other quantization methods must explicitly specify an oversample value either in the field mapping or at query time.
* **Rescoring**: Use the original vector values for re-calculating the score on the oversampled candidates.

As the non-quantized, original vectors are used to calculate the final score on the top results, rescoring combines:
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