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Ankur commented on MAHOUT-305:
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CooccurrenceCombiner caches items internally and increments
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Ankur commented on MAHOUT-305:
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But the answer is the partitioner ?
Yes
Am I right that
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Ankur commented on MAHOUT-344:
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Drew, thanks for pitching in as I've been running super busy
Minhash based clustering
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Key: MAHOUT-344
URL: https://issues.apache.org/jira/browse/MAHOUT-344
Project: Mahout
Issue Type: Bug
Components: Clustering
Reporter: Ankur
Minhash clustering
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Ankur updated MAHOUT-344:
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Affects Version/s: 0.3
Assignee: Ankur
Minhash based clustering
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Ankur updated MAHOUT-344:
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Attachment: MAHOUT-344-v1.patch
As per Yonik's law of patches submitting my implementation. Please feel free
to
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Ankur commented on MAHOUT-320:
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Binary comparison looks more or less the same in both the
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Ankur commented on MAHOUT-320:
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And yes I see the issue with (firstb1 - firstb2) thing in
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Ankur commented on MAHOUT-320:
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Robin, Can you update your revision and create a fresh patch ?
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Ankur commented on MAHOUT-320:
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It still complains that it cannot find the file to patch -
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Ankur commented on MAHOUT-305:
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Just picking random N % data for each user calculating avg
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Ankur commented on MAHOUT-305:
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I am not proposing that we choose random subset over all
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Ankur commented on MAHOUT-305:
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Well! not factoring ratings in the similarity metric but
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Ankur commented on MAHOUT-305:
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*smile* There we go.
Our last steps are essentially
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Ankur commented on MAHOUT-305:
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Sean, Thanks for filing the jira. Nothing points from our
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Ankur commented on MAHOUT-305:
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Hey Sean,
Have you played with netflix dataset?
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Ankur reassigned MAHOUT-305:
Assignee: Ankur
Combine both cooccurrence-based CF M/R jobs
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Ankur commented on MAHOUT-305:
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Typically when doing train-test data split, we divide the data
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Ankur commented on MAHOUT-305:
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With co-occurrence analysis we are dropping ratings. So if
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Ankur commented on MAHOUT-103:
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I skimmed through your version and what's present in .item
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Ankur edited comment on MAHOUT-103 at 12/23/09 12:41 PM:
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I skimmed
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Ankur commented on MAHOUT-103:
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Your changes don't look too mutating and yes roughly speaking
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Ankur commented on MAHOUT-103:
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Evolving the code to integrate better with the existing stuff
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Ankur commented on MAHOUT-103:
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Ok, so here is the next version which I again re-wrote
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Ankur updated MAHOUT-103:
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Attachment: run.sh
prepare.pl
mahout-103.patch.v2
Co-occurence based nearest
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Ankur updated MAHOUT-103:
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Attachment: (was: jira-103.patch)
Co-occurence based nearest neighbourhood
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Ankur commented on MAHOUT-103:
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For this co-occurrence based recommender I am planning to
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Ankur updated MAHOUT-103:
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Attachment: mahout-103.patch.v1
Ok, so here's the revised version of the algorithm that this jira proposes to
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Ankur commented on MAHOUT-103:
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Thanks for the quick lookup, appreciate that :-).
Putting in
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Ankur commented on MAHOUT-103:
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Re-post an updated patch
Sure I'll have the updated code
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Ankur commented on MAHOUT-103:
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In that case dropping ratings might not be such a good idea
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Ankur commented on MAHOUT-103:
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Hey Sean, Thanks for review comments. Some specific questions
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Ankur reassigned MAHOUT-103:
Assignee: Ankur
Co-occurence based nearest neighbourhood
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Ankur updated MAHOUT-103:
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Attachment: jira-103.patch
Ok here is a quick patch with just enough documentation and no unit tests or
dummy
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Ankur commented on MAHOUT-103:
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I hoping to make the above improvements after I get some
Co-occurence based nearest neighbourhood
Key: MAHOUT-103
URL: https://issues.apache.org/jira/browse/MAHOUT-103
Project: Mahout
Issue Type: New Feature
Components: Collaborative Filtering
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Ankur commented on MAHOUT-19:
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Hi Karl, Welcome back :-)
Can you share the following few things
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Ankur updated MAHOUT-4:
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Attachment: (was: Mahout_EM.patch)
Simple prototype for Expectation Maximization (EM)
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Ankur updated MAHOUT-4:
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Attachment: (was: PLSI_EM.patch)
Simple prototype for Expectation Maximization (EM)
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Ankur updated MAHOUT-4:
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Attachment: Mahout_EM.patch
Oops! Looks like my Subversive Eclipse plugin did something whacky while
generating the
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