[jira] [Commented] (LUCENE-7996) Should we require positive scores?

["Doug Turnbull (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/LUCENE-7996?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16278893#comment-16278893 ] 

Doug Turnbull commented on LUCENE-7996:
---------------------------------------

Just FYI for upstream impact, LTR models tend to output negative scores. For example Ranklib gradient boosting models range from -100 to 100. Of course this can be changed by always adding 100 to the score, but there's appeal in seeing the expected score from an LTR query being identical to the score you'd get from the model if you ran it outside of Solr/Elasticsearch.

> Should we require positive scores?
> ----------------------------------
>
>                 Key: LUCENE-7996
>                 URL: https://issues.apache.org/jira/browse/LUCENE-7996
>             Project: Lucene - Core
>          Issue Type: Wish
>            Reporter: Adrien Grand
>            Priority: Minor
>         Attachments: LUCENE-7996.patch, LUCENE-7996.patch, LUCENE-7996.patch
>
>
> Having worked on MAXSCORE recently, things would be simpler if we required that scores are positive. Practically, this would mean 
>  - forbidding/fixing similarities that may produce negative scores (we have some of them)
>  - forbidding things like negative boosts
> So I'd be curious to have opinions whether this would be a sane requirement or whether we need to be able to cope with negative scores eg. because some similarities that we want to support produce negative scores by design.



--
This message was sent by Atlassian JIRA
(v6.4.14#64029)

---------------------------------------------------------------------
To unsubscribe, e-mail: dev-unsubscribe@lucene.apache.org
For additional commands, e-mail: dev-help@lucene.apache.org