Thank you very much for your feedback!
Does there also exist an "ef" value inside Lucene
"ef - *the size of the dynamic list for the nearest neighbors* (used
during the search). Higher ef leads to more accurate but slower search.
ef cannot be set lower than the number of queried nearest neighbors k .
The value ef of can be anything between k and the size of the dataset."
or is the "k" value *the* "ef" value?
IIUC the relevant "k" value (k1) for the HNSW algorithm is what is set at
Query query = new KnnFloatVectorQuery("vector-field-name",queryVector, k1);
and not the max top docs value (k2) at
TopDocs topDocs = searcher.search(query, k2);
right?
But it should be k2 <= k1, right? Or would you set k1 == k2?
Thanks
Michael
Am 03.08.23 um 19:49 schrieb Michael Sokolov:
well, it is "approximate" KNN and can get caught in local minima
(maxima?). Increasing K has, indirectly, the effect of expanding the
search space because the minimum score in the priority score (score of
the Kth item) is used as a threshold for deciding when to terminate
the search
On Wed, Aug 2, 2023 at 5:19 PM Michael Wechner
<michael.wech...@wyona.com> wrote:
Hi
I use Lucene 9.7.0 but experienced the same behaviour with Lucene 9.6.0
when doing vector search as follows:
I have indexed about 200 vectors (dimension 768)
I build the query as follows
Query query = new KnnFloatVectorQuery("vector-field-name",
queryVector, k);
and do the search as follows:
TopDocs topDocs = searcher.search(query, k);
When I set k=27 then the top doc has a score of 0.7757
When I set the "k" value a little lower, e.g. k=24 then the top doc has
a score of 0.7319 and is not the same document as the one with the score
of 0.7757
And idea what I might be doing wrong or what I misunderstand?
Why does the value of k has an effect on the returned top doc?
Thanks
Michael
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