The reason is that sparse implementations may have recorded a non-zero that
later got assigned a zero, but they didn't bother to remove the memory cell.
On Thu, Jun 12, 2014 at 9:50 AM, Sebastian Schelter <s...@apache.org> wrote:
> I'm a bit lost in this discussion. Why do we assume that
> getNumNonZeroElements() on a Vector only returns an upper bound? The code
> in AbstractVector clearly returns the non-zeros only:
>
> int count = 0;
> Iterator<Element> it = iterateNonZero();
> while (it.hasNext()) {
> if (it.next().get() != 0.0) {
> count++;
> }
> }
> return count;
>
> On the other hand, the internal code seems broken here, why does
> iterateNonZero potentially return 0's?
>
> --sebastian
>
>
>
>
>
>
> On 06/12/2014 06:38 PM, ASF GitHub Bot (JIRA) wrote:
>
>>
>> [ https://issues.apache.org/jira/browse/MAHOUT-1464?page=
>> com.atlassian.jira.plugin.system.issuetabpanels:comment-
>> tabpanel&focusedCommentId=14029345#comment-14029345 ]
>>
>> ASF GitHub Bot commented on MAHOUT-1464:
>> ----------------------------------------
>>
>> Github user dlyubimov commented on the pull request:
>>
>> https://github.com/apache/mahout/pull/12#issuecomment-45915940
>>
>> fix header to say MAHOUT-1464, then hit close and reopen, it will
>> restart the echo.
>>
>>
>> Cooccurrence Analysis on Spark
>>> ------------------------------
>>>
>>> Key: MAHOUT-1464
>>> URL: https://issues.apache.org/jira/browse/MAHOUT-1464
>>> Project: Mahout
>>> Issue Type: Improvement
>>> Components: Collaborative Filtering
>>> Environment: hadoop, spark
>>> Reporter: Pat Ferrel
>>> Assignee: Pat Ferrel
>>> Fix For: 1.0
>>>
>>> Attachments: MAHOUT-1464.patch, MAHOUT-1464.patch,
>>> MAHOUT-1464.patch, MAHOUT-1464.patch, MAHOUT-1464.patch, MAHOUT-1464.patch,
>>> run-spark-xrsj.sh
>>>
>>>
>>> Create a version of Cooccurrence Analysis (RowSimilarityJob with LLR)
>>> that runs on Spark. This should be compatible with Mahout Spark DRM DSL so
>>> a DRM can be used as input.
>>> Ideally this would extend to cover MAHOUT-1422. This cross-cooccurrence
>>> has several applications including cross-action recommendations.
>>>
>>
>>
>>
>> --
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>>
>>
>
