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https://issues.apache.org/jira/browse/MAHOUT-668?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13037504#comment-13037504
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Ted Dunning commented on MAHOUT-668:
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{quote}
Your right. The distance metrics will have trouble with Random Vectors. I'll
work on a fix for that. (The code is on the critical path, I can't afford to
lose the speed of the current method and the other vector methods give
incorrect results for missing=0 vectors)
{quote}
Sparse vectors in Mahout assume that missing elements are 0.
Are you saying that you want to consider missing elements as something other
than 0? Your javadoc didn't seem to say that.
You should get the same results either way.
> Adding knn support to Mahout classifiers
> ----------------------------------------
>
> Key: MAHOUT-668
> URL: https://issues.apache.org/jira/browse/MAHOUT-668
> Project: Mahout
> Issue Type: Improvement
> Components: Classification
> Affects Versions: 0.6
> Reporter: Daniel McEnnis
> Labels: classification, knn
> Attachments: MAHOUT-668.pat, Mahout-668-2.patch, Mahout-668-3.patch,
> Mahout-668.pat
>
> Original Estimate: 672h
> Remaining Estimate: 672h
>
> Initial implementation of the knn. This is a minimum base set with many more
> possible add-ons including support for text and weka input as well as a
> classify only (no confusion matrix) back end. The system was tested on the
> 20 newsgroup data set.
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