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https://issues.apache.org/jira/browse/LUCENE-7997?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Robert Muir updated LUCENE-7997:
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Attachment: LUCENE-7997_wip.patch
Patch randomizing values of parameters, adding missing range checks/docs for
these parameters. These are just the valid ranges documented by the formulas,
for unbounded parameters (such as normalization c, smoothing parameter mu) we
treat them the same as BM25's k1 and just ensure non-negative/finite in the
range check, and test the range of 0..Integer.MAX_VALUE.
Still TODO is axiomatic parameters, need to look at paper and existing code (it
has some range checks already so it may be easy).
> More sanity testing of similarities
> -----------------------------------
>
> Key: LUCENE-7997
> URL: https://issues.apache.org/jira/browse/LUCENE-7997
> Project: Lucene - Core
> Issue Type: Task
> Reporter: Adrien Grand
> Priority: Minor
> Attachments: LUCENE-7997_wip.patch, LUCENE-7997_wip.patch,
> LUCENE-7997_wip.patch, LUCENE-7997_wip.patch, LUCENE-7997_wip.patch,
> LUCENE-7997_wip.patch, LUCENE-7997_wip.patch, LUCENE-7997_wip.patch,
> LUCENE-7997_wip.patch, LUCENE-7997_wip.patch
>
>
> LUCENE-7993 is a potential optimization that we could only apply if the
> similarity is an increasing functions of {{freq}} (all other things like DF
> and length being equal). This sounds like a very reasonable requirement for a
> similarity, so we should test it in the base similarity test case and maybe
> move broken similarities to sandbox?
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