Hi Adrien
Thanks for your feedback! Whereas I am not sure I fully understand what
you mean
At the moment I am using something like:
float[] vector = ...;
FieldType vectorFieldType = KnnVectorField.createFieldType(vector.length,
VectorSimilarityFunction.COSINE);
KnnVectorField vectorField =new KnnVectorField("vector_field", vector,
vectorFieldType);
doc.add(vectorField);
Could you give me some sample code what you mean with "custom KNN
vectors format"?
Thanks
Michael
Am 14.01.23 um 22:14 schrieb Adrien Grand:
Hi Michael,
You could create a custom KNN vectors format that ignores the vector
similarity configured on the field and uses its own.
Le sam. 14 janv. 2023, 21:33, Michael Wechner<michael.wech...@wyona.com> a
écrit :
Hi
IIUC Lucene currently supports
VectorSimilarityFunction.COSINE
VectorSimilarityFunction.DOT_PRODUCT
VectorSimilarityFunction.EUCLIDEAN
whereas some embedding models have been trained with other metrics.
Also see
https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.distance.cdist.html
How can I best implement another metric?
Thanks
Michael
---------------------------------------------------------------------
To unsubscribe, e-mail:java-user-unsubscr...@lucene.apache.org
For additional commands, e-mail:java-user-h...@lucene.apache.org
