Comments (4)
Hi @sephib thanks for submitting. Thiago will get back on this, it will take some days as he is not working on this right now
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Yes, it makes sense when you want to rank only specific document ids. I will add an example as suggested.
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Hi @sephib, I am not sure if using recall
in this use-case makes sense. When you call evaluate_query
you want to evaluate the results returned by a specific query_model
for a given query
.
Using recall
here will contaminate the evaluation results by potentially including documents that wouldn't otherwise be returned by the query model. Am I missing something?
from pyvespa.
you are also correct -
but on the other hand - sometimes you want to confine the evaluation to a set of documents - especially when working with NDCG metric.
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Related Issues (20)
- Access to user query in reranking phase when using approximate neighbor search HOT 1
- Use rank profile inputs HOT 4
- What about increasing the minimum required Python version? HOT 1
- Add field to schema HOT 2
- No document can be fed because ostensibly there isn't enough disk space HOT 7
- Allow to add configuration to content HOT 2
- Dependency Dashboard
- Types for RankProfile.inputs HOT 1
- VespaSync::delete_all_docs only makes a single delete call HOT 1
- Better feed implementation/interface HOT 1
- Deprecation of PyVespa functionality HOT 1
- Add support for mode streaming with pyvespa HOT 1
- Add support for node resource specification and count
- Remove dependency on pandas
- Struct inconsistencie HOT 3
- Deploy with docker compose and similar setup vespa to other vector dbs HOT 5
- Manually deployed vespa with docker compose Failed to establish a new connection: [Errno 111] HOT 15
- clear explanation where does the docker container stores files HOT 1
- Type hint of RankProfile inputs HOT 3
- Make `add_fields()` method of `Schema` add them outside of document. HOT 1
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