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This repository has been archived by the owner on May 1, 2020. It is now read-only.
Thanks a lot for implement!
Where is the API which can change the value of w according to the paper in python implement(not spark)?
And what is the default value of w in your implement?
Looking forward for your reply!
The text was updated successfully, but these errors were encountered:
The parameter w from the paper is the number of coarse quantizer cells to retrieve for a query before reranking. This implementation instead uses the concept of a result "quota" — it will retrieve as many cells as needed to meet a result quota before reranking. If you want to specify a fixed number of cells, you will need to implement this yourself. See the search code for the current quota-based implementation: https://github.com/yahoo/lopq/blob/master/python/lopq/search.py#L101-L125
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Thanks a lot for implement!
Where is the API which can change the value of w according to the paper in python implement(not spark)?
And what is the default value of w in your implement?
Looking forward for your reply!
The text was updated successfully, but these errors were encountered: