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https://issues.apache.org/jira/browse/MAHOUT-1541?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14051741#comment-14051741
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ASF GitHub Bot commented on MAHOUT-1541:
----------------------------------------
Github user pferrel commented on the pull request:
https://github.com/apache/mahout/pull/22#issuecomment-47960471
The discrepancy between Spark and mrlegacy is in the final output value
from the legacy code
```
return 1.0 - 1.0 / (1.0 + logLikelihood);
```
This produces the same results for spark and mrlegacy so i'll go with it
but would love an explanation.
> Create CLI Driver for Spark Cooccurrence Analysis
> -------------------------------------------------
>
> Key: MAHOUT-1541
> URL: https://issues.apache.org/jira/browse/MAHOUT-1541
> Project: Mahout
> Issue Type: New Feature
> Components: CLI
> Reporter: Pat Ferrel
> Assignee: Pat Ferrel
>
> Create a CLI driver to import data in a flexible manner, create an
> IndexedDataset with BiMap ID translation dictionaries, call the Spark
> CooccurrenceAnalysis with the appropriate params, then write output with
> external IDs optionally reattached.
> Ultimately it should be able to read input as the legacy mr does but will
> support reading externally defined IDs and flexible formats. Output will be
> of the legacy format or text files of the user's specification with
> reattached Item IDs.
> Support for legacy formats is a question, users can always use the legacy
> code if they want this. Internal to the IndexedDataset is a Spark DRM so
> pipelining can be accomplished without any writing to an actual file so the
> legacy sequence file output may not be needed.
> Opinions?
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