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https://issues.apache.org/jira/browse/MAHOUT-682?focusedWorklogId=995944&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-995944
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ASF GitHub Bot logged work on MAHOUT-682:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 12/Dec/25 10:50
Start Date: 12/Dec/25 10:50
Worklog Time Spent: 10m
Work Description: shiavm006 opened a new pull request, #724:
URL: https://github.com/apache/mahout/pull/724
### Purpose of PR
document missing QuMat APIs: `apply_cswap_gate`, `apply_t_gate`,
`get_final_state_vector`, `apply_u_gate`, `swap_test`, `measure_overlap`; align
API docs with currently implemented methods in `qumat.QuMat`
### Related Issues or PRs
Closes #682
### Changes Made
<!
Issue Time Tracking
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Worklog Id: (was: 995944)
Remaining Estimate: 0h
Time Spent: 10m
> The LDA output does not include the topic-probability distribution per
> document (p(z|d)). It outputs only the topics and corresponding words.
> ---------------------------------------------------------------------------------------------------------------------------------------------
>
> Key: MAHOUT-682
> URL: https://issues.apache.org/jira/browse/MAHOUT-682
> Project: Mahout
> Issue Type: Improvement
> Components: classic
> Affects Versions: 0.4
> Reporter: Himanshu Gahlot
> Assignee: Jake Mannix
> Priority: Major
> Fix For: 0.5
>
> Attachments: ASF.LICENSE.NOT.GRANTED--MAHOUT-458.patch,
> ASF.LICENSE.NOT.GRANTED--MAHOUT-458.patch
>
> Time Spent: 10m
> Remaining Estimate: 0h
>
> The current implementation of LDA outputs only topics and their words. Many
> applications need the p(z|d) values of a document to use this vector as a
> reduced representation of the document (dimensionality reduction of
> document). We need to introduce a new key which would keep track of the gamma
> values for each document (as obtained from the document.infer() method) and
> writes these to the output stream and finally, PrintLDATopics should output
> these values per document id. Also, outputting the probabilities of words in
> a topic would also provide a more meaningful output.
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